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                <title>Corporate Communication on Twitter in Slovenia: A Corpus Analysis</title>
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                    <name>
                        <forename>Darja</forename>
                        <surname>Fišer</surname>
                        <affiliation>Department of Translation, Faculty of Arts, University of
                            Ljubljana</affiliation>
                        <address>
                            <addrLine>Aškerčeva 2</addrLine>
                            <addrLine>SI-1000 Ljubljana</addrLine>
                        </address>
                        <email>Darja.fiser@ff.uni-lj.si</email>
                        <affiliation>Department of Knowledge Technologies, Jožef Stefan
                            Institute</affiliation>
                        <address>
                            <addrLine>Jamova cesta 39</addrLine>
                            <addrLine>SI-1000 Ljubljana</addrLine>
                        </address>
                    </name>
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                <edition><date>2019-04-15</date></edition>
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                <publisher>
                    <orgName xml:lang="sl">Inštitut za novejšo zgodovino</orgName>
                    <orgName xml:lang="en">Institute of Contemporary History</orgName>
                    <address>
                        <addrLine>Kongresni trg 1</addrLine>
                        <addrLine>SI-1000 Ljubljana</addrLine>
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                <pubPlace>http://ojs.inz.si/pnz/article/view/338</pubPlace>
                <date>2019</date>
                <availability status="free">
                    <licence>http://creativecommons.org/licenses/by-nc-nd/4.0/</licence>
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                <title xml:lang="sl">Prispevki za novejšo zgodovino</title>
                <title xml:lang="en">Contributions to Contemporary History</title>
                <biblScope unit="volume">59</biblScope>
                <biblScope unit="issue">1</biblScope>
                <idno type="ISSN">2463-7807</idno>
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                <p>Contributions to Contemporary History is one of the central Slovenian scientific
                    historiographic journals, dedicated to publishing articles from the field of
                    contemporary history (the 19th and 20th century).</p>
                <p>The journal is published three times per year in Slovenian and in the following
                    foreign languages: English, German, Serbian, Croatian, Bosnian, Italian, Slovak
                    and Czech. The articles are all published with abstracts in English and
                    Slovenian as well as summaries in English.</p>
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                <p>Prispevki za novejšo zgodovino je ena osrednjih slovenskih znanstvenih
                    zgodovinopisnih revij, ki objavlja teme s področja novejše zgodovine (19. in 20.
                    stoletje).</p>
                <p>Revija izide trikrat letno v slovenskem jeziku in v naslednjih tujih jezikih:
                    angleščina, nemščina, srbščina, hrvaščina, bosanščina, italijanščina, slovaščina
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                <keywords xml:lang="en">
                    <term>corporate communication</term>
                    <term>social media</term>
                    <term>Twitter</term>
                    <term>corpus analysis</term>
                </keywords>
                <keywords xml:lang="sl">
                    <term>korporativno komuniciranje</term>
                    <term>družbena omrežja</term>
                    <term>Twitter</term>
                    <term>korpusna analiza</term>
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        <front>
            <docAuthor>Darja Fišer<note place="foot" xml:id="ftn1" n="*">Department of Translation,
                    Faculty of Arts, University of Ljubljana, Aškerčeva 2, SI-1000 Ljubljana,
                    Department of Knowledge Technologies, Jožef Stefan Institute, Jamova cesta 39,
                    SI-1000 Ljubljana, Darja.fiser@ff.uni-lj.si</note></docAuthor>
            <docAuthor> Monika Kalin Golob<note place="foot" xml:id="ftn2" n="**">Chair of
                    Journalism, Faculty of Social Sciences, University of Ljubljana, Kardeljeva
                    ploščad 5, SI-1000 Ljubljana, monika.kalin-golob@fdv.uni-lj.si</note>
            </docAuthor>
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                <idno type="UDC">UDC: 003.295:659.4+004.738.5(497.4) )"201"</idno>
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            <div type="abstract" xml:lang="sl">
                <head>IZVLEČEK</head>
                <head>SLOVENSKO KORPORATIVNO SPOROČANJE NA DRUŽBENEM OMREŽJU TWITTER: KORPUSNA
                    ANALIZA</head>
                <p>
                    <hi rend="italic">V prispevku predstavimo korpusno analizo korporativnega
                        komuniciranja na družbenem omrežju Twitter, ki smo jo s kombinacijo
                        besedilnih in metapodatkov izvedli na korpusu Janes-Tweet. Analizirali smo
                        značilnosti slovenskih korporativnih računov in dinamiko njihovih objav ter
                        analizirali rabo novomedijskih elementov in uporabljenega jezika v
                        korporativnih objavah. Na koncu smo proučili še ključne besede v
                        korporativnih objavah. Izvedene analize so pokazale, da v primerjavi z
                        zasebnimi računi v korporativnih tvitih izrazito prevladujejo standardne
                        jezikovne prvine formalnega sporočanja, sicer redkejše neformalne in
                        nestandardne izbire pa so uporabljene premišljeno glede na naslovnika
                        sporočila in namen sporočanja. Prispevek je dragocen tudi zato, ker
                        demonstrira potencial korpusnih pristopov v komunikologiji, medijskih
                        študijah in drugih sorodnih družboslovnih disciplinah, ki proučujejo
                        jezikovno rabo.</hi></p>
                <p><hi rend="italic">Ključne besede: korporativno komuniciranje, družbena omrežja,
                        Twitter, korpusna analiza</hi></p>
            </div>
            <div type="abstract">
                <head style="text-transform: uppercase;">Abstract</head>
                <p>
                    <hi rend="italic">The paper presents a corpus analysis of
                        corporate communication on Twitter, which was performed with a combination
                        of metadata and textual data on the Janes-Tweet corpus. We compare the
                        amount, posting dynamics and use of social-media specific communication
                        elements by Slovene corporate and private users. Next, we analyse the
                        language of corporate users. Our analysis shows that, in comparison to
                        private accounts, corporate tweets predominantly use formal communication
                        and standard language characteristics with seldom usage of informal and
                        non-standard choices. In the event of those, however, they are chosen
                        deliberately to address a specific target audience and meet the desired
                        communicative goals. A major contribution of the paper is also a showcase of
                        corpus-based approaches in communication studies, media studies and other
                        related disciplines in social sciences which study language use.</hi></p>
                <p>
                    <hi rend="italic">Keywords: corporate communication,
                        social media, Twitter, corpus analysis</hi></p>
            </div>
        </front>
        <body>
            <div>
                <head>Introduction</head>
                <p>In the past decade, social media have evolved into a powerful tool, attracting
                    millions of users every day (<ref target="#Boyd.2007">Boyd and Ellison 2007</ref>).
                    <ref target="#Jansen.2010">Jansen et al. (2010)</ref> have
                    shown that around 20 percent of all published tweets mentioned or expressed
                    their opinion about an organization, brand, product or service. What is more, 
                    <ref target="#Wu.2011">Wu et al. (2011)</ref> show that this new form of electronic word-of-mouth is
                    approximately 20 times more effective than marketing events and 30 times more
                    effective than media appearances. It is therefore unsurprising to see such a
                    rapid growth of the online social media marketing (<ref target="#Griffiths.2014">Griffiths and McLean 2014</ref>)
                    through which companies address a wide range of goals, such as increased traffic
                    and brand awareness, improved search engine rankings or increased sales (<ref target="#Thoring.2011">Thoring
                    2011</ref>). In addition, social media can also be used for customer service and
                    market research (<ref target="#Weber.2009">Weber 2009</ref>).</p>
                <p>With the growing commercial relevance of social media, researchers have begun to
                    study the nature and influence of corporate communication on social media.
                    Researchers who investigate the patterns of how information spreads through the
                    Twitter network showed that tweets which contain URLs tend to spread faster
                    (<ref target="#Park.2012">Park et al. 2012</ref>) and that tweets containing words which indicate either
                    positive or negative sentiment tend to receive more retweets than neutral posts
                    (<ref target="#Stieglitz.2012">Stieglitz and Dang-Xuan 2012</ref>). 
                    <ref target="#Stelzner.2010">Stelzner (2010)</ref> and <ref target="#Heaps.2009">Heaps (2009)</ref> showed that
                    marketers use social media mainly for generating exposure for their business and
                    increasing traffic to their corporate websites, rather than for selling products
                    and services. Evidence has also been found that social media have a positive
                    effect on increasing relational outcomes, such as online reputation and
                    relationship strength (<ref target="#Clark.2013">Clark and Melancon 2013</ref>; 
                    <ref target="#Li.2013">Li et al. 2013</ref>; <ref target="#Miller.2013">Miller and
                    Tucker 2013</ref>). It is therefore surprising that while the new platform of
                    engagement with customers has shifted the company–customer discourse, <ref target="#Mangold.2009">Mangold
                    and Faulds (2009)</ref> show that communication is still predominantly scripted,
                    promotion-centric and lacks real interaction with the customers.</p>
                <p>In this paper we present the results of the first large-scale analysis of
                    corporate communication on Twitter in Slovenia. We look into the production,
                    dynamics and language in the tweets of Slovene corporate users in order to
                    identify the characteristics of such communication in contrast to the
                    communication of private Twitter users. In our study, we use the term corporate
                    account for all private companies, public institutions, the media and interest
                    associations who do not post as individuals for leisure purposes. The analysis
                    was performed on the corpus Janes-Tweet (<ref target="#Erjavec.2018">Erjavec et al. 2018</ref>) by combining the
                    available user and text metadata with the content of the tweets, which enabled a
                    more accurate contextualization, parametrization, comparison and generalizations
                    of language use in a specific communicative context.</p>
                <p>The rest of the paper is structured as follows: in Section 2 we present related
                    work relevant for our study, in section 3, we present the results of the corpus
                    analysis and Section 4 concludes the paper and outlines future work.</p>
            </div>
            <div>
                <head>Related Work</head>
                <p>In communication studies, three main strands of research into corporate social
                    media communication practices can be identified. The first group focuses on
                    investigating posting behaviour, the second looks into content analysis, and the
                    third are perception studies. In terms of research focus, investigators are
                    mostly interested in corporate communication styles, reputation management and
                    corporate social responsibility.</p>
                <p>Quantitative differences in communication dynamics, style and content of Slovene
                    private and corporate Twitter users have been identified by <ref target="#Ljubešić.2016">Ljubešić and Fišer
                    (2016)</ref> and have been attributed to the different communication functions of
                    private and corporate social media users. While corporate users mostly tweet
                    during the work week in the morning, private users are more active during
                    weekends and in the evening. Corporate tweets have distinctly positive
                    sentiment, while private tweets are predominantly neutral. Tweets posted by
                    corporate users are retweeted much more often while private tweets are more
                    frequently favourited.</p>
                <p>By analyzing tweet frequency, following behavior, hyperlinks, hashtags, mentions
                    and retweets, several studies have shown that one-way communication is still the
                    most common communication strategy used by organizations on Twitter (<ref target="#Waters.2011">Waters and
                    Jamal 2011</ref>; <ref target="#Xifra.2010">Xifra and Grau 2010</ref>) and that the style and genre in tweets by PR
                    professionals is the same as in other PR text types, treating social media as
                    yet another channel for reaching a different consumer segment, without adapting
                    their language accordingly (<ref target="#KalinGolob.2018">Kalin Golob et al. 2018</ref>).
                    However, as shown by <ref target="#Kwon.2011">Kwon
                    and Sung (2011)</ref>, the growing frequency of imperative verb phrases, such as
                    "follow the brand," "come by the booth," "join us at the event," or "sign up"
                    for a planned occasion, suggest that corporations increasingly use Twitter as a
                    tool to initiate and maintain relationships with consumers. <ref target="#Risius.2015">Risius and Beck
                    (2015)</ref> empirically identified social media activities in terms of social media
                    management strategies (using social media management tools or the web-frontend
                    client), account types (broadcasting or receiving information), and
                    communicative approaches (conversational or disseminative). They found positive
                    effects of social media management tools, broadcasting accounts, and
                    conversational communication on public perception. Company account
                    characteristics that have been found to influence public perception are
                    verification, friends, and status.</p>
                <p><ref target="#Gomez.2013">Gomez and Chalmeta (2013)</ref> used content analysis to look into corporate social
                    responsibility (CSR) on social media and have identified presentation, content,
                    and interactivity as the key resources for CSR communication on social media.
                    Presentation refers to the different tools and basic information that supports
                    the company’s CSR presence on social media. Content includes messages related to
                    CSR and other topics that reinforce the communication of CSR practices.
                    Interactivity refers to the type of CSR communication and the frequency of CSR
                    messages and feedback.</p>
                <p><ref target="#Li.2013">Li et al. (2013)</ref> used social identity theory to identify design factors that
                    determine the social context of a corporate Twitter channel and users’ social
                    identification with the community. They confirm that user engagement and
                    informedness in a corporate Twitter channel have a positive effect on corporate
                    reputation and that the credibility of the corporate Twitter channel has a
                    positive effect on user informedness about the corporation. An interesting
                    finding is that deeper relationships among users of a corporate Twitter channel
                    result in higher user engagement and informedness when the level of corporate
                    involvement with the channel is high and the channel has a specific purpose but
                    that the opposite is true when the channel has a generic purpose.</p>
                <p>In the related work, post harvesting is typically tailor-made and small-scale,
                    either focused on a few carefully selected corporate social media accounts (e.g.
                    3 companies), or limited to a carefully designed time span (e.g. 1 month).
                    Coding of the observed phenomena is manual. The research framework is
                    quantitative but done on a relatively small scale, and experimental in that
                    research hypotheses are confirmed or rejected with statistical tests. Our work
                    differs from this research framework in that we use an existing large corpus of
                    tweets and are interested in the characteristics of all the available corporate
                    accounts in it. While coding of certain phenomena (e.g. account type, user
                    gender) was manual, it was performed prior to this study by coders unrelated to
                    this study, so could not be fully controlled. Coding of many other phenomena
                    (e.g. language, sentiment and standardness level of tweets) was automatic and
                    therefore contains a certain degree of noise. Our approach is not only
                    quantitative but large scale as well, taking into account several thousands of
                    users and several million of their tweets, and is descriptive in nature. What is
                    more, unlike most related work which mostly observe the metadata (e.g. tweet
                    frequency, following behavior, retweets) or content of the messages (e.g.
                    hyperlinks, hashtags, mentions, sentiment), we also perform an analysis of the
                    language used in the messages, which is still underresearched in communication
                    studies. A better understanding of the language practices used by public
                    companies and institutions for presentation, persuasion and reputation
                    management on social media will contribute towards a comprehensive understanding
                    of contemporary, technology-enhanced corporate public relations and marketing
                    strategies and practices. Finally, while most researchers focus almost
                    exlusively on English, our study is performed on Slovene which can serve as a
                    showcase for other languages with a smaller number of speakers (and therefore a
                    smaller market size the corporate accounts are serving).</p>
            </div>
            <div>
                <head>Corpus Analysis of Corporate Communication on Twitter</head>
                <p>The analysis has been performed on the Janes-Tweet corpus (<ref target="#Erjavec.2018">Erjavec et al. 2018</ref>)
                    consisting of 11.3 million Slovene tweets or 160 million tokens published by
                    more than 10,200 users. Depending on their communication purpose, users in the
                    corpus are manually divided into two groups: private and corporate. Corporate
                    accounts comprise all private companies, public institutions, the media and
                    interest associations who do not post as individuals for leisure purposes, who
                    are treated as private accounts. In order to establish the characteristics of
                    corporate communication on Twitter and differentiate them from the common
                    practices typical of this medium in general, we perform a contrastive analysis
                    of these two types of accounts.</p>
                <p>Our study consists of three parts, each of which addresses a major segment of
                    communication styles on Twitter, ranging from the analysis of communication
                    dynamics and metadata to the content and language analysis, observed from the
                    perspective of the two types of accounts. First, we analyzed the production and
                    posting dynamics of these two user groups. Next, we analyzed the use of social
                    media-specific communication elements, such as hashtags, emojis and emoticons.
                    Finally, we analyzed the language and keywords used in corporate tweets. All the
                    analyses were performed in the SketchEngine corpus-analysis<note place="foot" xml:id="ftn3" n="1">The corpus is publically available for <ref target="https://www.clarin.si/repository/xmlui/handle/11356/1142">download</ref> as well as for <ref target="https://www.clarin.si/noske/run.cgi/corp_info?corpname=janes_tweet">on-line querying</ref> through the CLARIN.SI research
                        infrastructure.</note> suite (<ref target="#Kilgarriff.2014">Killgarriff et al. 2014</ref>).</p>
                <p>The research questions we address with each part of our study are: 1) Does
                    corporate communication on Twitter by Slovene users have a distinct corporate
                    profile in terms of posting dynamics and volume? 2) Have Slovene corporate users
                    adopted the new media communication style and are using the features offered by
                    the new media to maximize their reach and relationship strength? 3) Can we
                    identify the Slovene corporate tweeting code?</p>
                <div>
                    <head>Account Analysis</head>
                    <table rend="table-scroll">
                        <head>Table 1: Share of corporate and private users and their production in
                            the Janes-Tweet corpus.</head>
                        <row role="label">
                            <cell>Users</cell>
                            <cell>No. of users (%)</cell>
                            <cell>No. of tokens (%)</cell>
                            <cell>No. of tweets (%)</cell>
                        </row>
                        <row>
                            <cell>Corporate</cell>
                            <cell style="text-align:right;">2612<lb/> (25.57%)</cell>
                            <cell style="text-align:right;">30,003,182<lb/> (18.70%)</cell>
                            <cell style="text-align:right;">2,112,910<lb/> (18.64%)</cell>
                        </row>
                        <row>
                            <cell>Private</cell>
                            <cell style="text-align:right;">7627<lb/> (74.44%)</cell>
                            <cell style="text-align:right;">130,401,083<lb/> (81.30%)</cell>
                            <cell style="text-align:right;">9,223,736<lb/> (81.36%)</cell>
                        </row>
                        <row>
                            <cell>Total</cell>
                            <cell style="text-align:right;">10,248<lb/> (10.00%)</cell>
                            <cell style="text-align:right;">160,404,265<lb/> (100.00%)</cell>
                            <cell style="text-align:right;">11,336,646<lb/> (100.00%)</cell>
                        </row>
                    </table>
                    <p>
                        <hi rend="bold">Share of users.</hi> The ratio between
                        private to corporate users in the corpus is 3:1. As can be seen in Table 1,
                        less than a fifth of all the tweets in the corpus have been posted by
                        corporate users. This means that in Slovenia, Twitter is mainly used for
                        private communication.</p>
                    <table rend="table-scroll">
                        <head>Table 2: Distribution of tweets by corporate and private users based
                            on gender in the Janes-Tweet corpus.</head>
                        <row role="label">
                            <cell style="border:0.5px solid #333333;" rows="2"> Gender</cell>
                            <cell style="border:0.5px solid #333333;" cols="2">Corporate</cell>
                            <cell style="border:0.5px solid #333333;" cols="2">Private</cell>
                        </row>
                        <row>
                            <cell style="border:0.5px solid #333333;">no. of tweets</cell>
                            <cell style="border:0.5px solid #333333;">%</cell>
                            <cell style="border:0.5px solid #333333;">no. of tweets</cell>
                            <cell style="border:0.5px solid #333333;">%</cell>
                        </row>
                        <row>
                            <cell>Unknown</cell>
                            <cell style="text-align:right;">1,730,258</cell>
                            <cell style="text-align:right;">81.89%</cell>
                            <cell style="text-align:right;">134,048</cell>
                            <cell style="text-align:right;">1.45%</cell>
                        </row>
                        <row>
                            <cell>Male</cell>
                            <cell style="text-align:right;">271,729</cell>
                            <cell style="text-align:right;">12.86%</cell>
                            <cell style="text-align:right;">6,136,470</cell>
                            <cell style="text-align:right;">66.53%</cell>
                        </row>
                        <row>
                            <cell>Female</cell>
                            <cell style="text-align:right;">110,923</cell>
                            <cell style="text-align:right;">5.25%</cell>
                            <cell style="text-align:right;">2,953,218</cell>
                            <cell style="text-align:right;">32.02%</cell>
                        </row>
                        <row>
                            <cell>Total</cell>
                            <cell style="text-align:right;">2,112,910</cell>
                            <cell style="text-align:right;">100.00%</cell>
                            <cell style="text-align:right;">9,223,736</cell>
                            <cell style="text-align:right;">100.00%</cell>
                        </row>
                    </table>
                    <p>
                        <hi rend="bold">Users’ gender.</hi> As shown in Table 2, gender could not be
                        determined for the majority of corporate users (82%) based on user name,
                        user profile data and verb form usage in their tweets, which is rare in the
                        case of private users (1.5%). This is unsurprising because corporate users
                        tweet on behalf of their company or organization, adapting their style of
                        writing accordingly, e.g. the use of first person plural verb forms, which
                        do not distinguish the gender of the writer. </p>
                </div>
                <div>
                    <head>Posting Analysis</head>
                    <p>
                        <hi rend="bold">Post quantity.</hi> There are only 29
                        (1%) corporate users who are very active on social media and have posted
                        over 10,000 tweets, and 422 (16%) medium-active ones with 1,000 – 10,000
                        tweets. The majority of corporate users (1,640 or 62.79%) fall into the
                        category of low-activity accounts with 100 – 1,000 tweets. The
                        lowest-activity group includes 521 users (19.95%) who have posted fewer than
                        100 tweets. In comparison to private users, the biggest difference is in
                        groups 2 and 4. There are 9% more private users with 1,000 – 10,000 tweets
                        and a similar percentage fewer private accounts with only 100 – 1,000
                        tweets. In the years included in the Janes-Tweet corpus, the volume of
                        content generated by the corporate users is stable but is decreasing
                        slightly among the private users (see Figure 1). Occasional sharp drops in
                        the number of posts, which are simultaneous for both user groups, were
                        caused by the technical issues during data collection and are not related to
                        the seasonal fluctuations or other content-related phenomena.</p>
                    <table rend="table-scroll">
                        <head>Table 3: Activity of corporate and private users in the Janes-Tweet
                            corpus.</head>
                        <row role="label">
                            <cell/>
                            <cell cols="2">Corporate</cell>
                            <cell cols="2">Private</cell>
                        </row>
                        <row>
                            <cell>No. of all accounts</cell>
                            <cell style="text-align:right;">2612</cell>
                            <cell style="text-align:right;">%</cell>
                            <cell style="text-align:right;">7627</cell>
                            <cell style="text-align:right;">%</cell>
                        </row>
                        <row>
                            <cell>&gt; 10,000 tweets</cell>
                            <cell style="text-align:right;">29</cell>
                            <cell style="text-align:right;">1.11%</cell>
                            <cell style="text-align:right;">129</cell>
                            <cell style="text-align:right;">1.69%</cell>
                        </row>
                        <row>
                            <cell>Between 10,000 and 1,000 tweets</cell>
                            <cell style="text-align:right;">422</cell>
                            <cell style="text-align:right;">16.16%</cell>
                            <cell style="text-align:right;">1867</cell>
                            <cell style="text-align:right;">24.48%</cell>
                        </row>
                        <row>
                            <cell>Between 1,000 and 100 tweets</cell>
                            <cell style="text-align:right;">1640</cell>
                            <cell style="text-align:right;">62.79%</cell>
                            <cell style="text-align:right;">4055</cell>
                            <cell style="text-align:right;">53.17%</cell>
                        </row>
                        <row>
                            <cell>&lt; 100 tweets</cell>
                            <cell style="text-align:right;">521</cell>
                            <cell style="text-align:right;">19.95%</cell>
                            <cell style="text-align:right;">1576</cell>
                            <cell style="text-align:right;">20.66%</cell>
                        </row>
                    </table>
                    <figure>
                        <head>Figure 1: Posting dynamics of corporate and private users in the
                            Janes-Tweet corpus. according to the number of posted tweets between
                            June 2013 and June 2017.</head>
                        <graphic url="image1.png"/>
                    </figure>
                    <p>
                        <hi rend="bold">Post length.</hi> Figure 2 shows that
                        the length of corporate tweets is more homogenous than the length of private
                        tweets. The biggest share of corporate tweets are 7 to 11 words long (4 to 7
                        words in case of private users). The share of corporate tweets which do not
                        contain any word (only emojis, hashtags, hyperlinks or multimedia elements)
                        is only 0.1%. Such tweets are six times more frequently produced by private
                        users, which is not surprising as these symbols are typically used in
                        bidirectional communication, which is rare in corporate PR tweets.</p>
                    <figure>
                        <head>Figure 2: Tweet length of corporate and private users in the
                            Janes-Tweet corpus.</head>
                        <graphic url="image2.png"/>
                    </figure>
                </div>
                <div>
                    <head>Analysis of Interactive Elements</head>
                    <p>
                        <hi rend="bold">Likes.</hi> As can be seen from Table 4, nearly 80% of
                        corporate tweets do not receive any likes, 12% have one like and only 9%
                        have 2 or more likes. Private tweets receive significantly different
                        attention: a third of all the private tweets is liked at least once and a
                        significant share of them (0.7%) receives over 10 likes. This is another
                        strong sign that bidirectional communication is less typical of corporate
                        users and that corporate tweets are just one of the channels of the same
                        type of (one-directional) communication disseminated through different
                        genres.</p>
                    <table rend="table-scroll">
                        <head>Table 4: Share of liked and retweeted tweets of corporate and private users
                            in the Janes-Tweet corpus.</head>
                        <row role="label" style="border-top:0.5px solid #333333;">
                            <cell cols="5">No. of likes</cell>
                        </row>
                        <row role="label">
                            <cell rows="2"/>
                            <cell style="border:0.5px solid #333333;" cols="2">Corporate users</cell>
                            <cell style="border:0.5px solid #333333;" role="label" cols="2">Private users</cell>
                        </row>
                        <row role="label" style="border-bottom:0.5px solid #333333;">
                            <cell style="border:0.5px solid #333333;">No. of tweets</cell>
                            <cell style="border:0.5px solid #333333;" role="label">%</cell>
                            <cell style="border:0.5px solid #333333;" role="label">No. of tweets</cell>
                            <cell style="border:0.5px solid #333333;" role="label">%</cell>
                        </row>
                        <row>
                            <cell>0</cell>
                            <cell style="text-align:right;">1,663,755</cell>
                            <cell style="text-align:right;">78.74%</cell>
                            <cell style="text-align:right;">610,9048</cell>
                            <cell style="text-align:right;">66.23%</cell>
                        </row>
                        <row>
                            <cell>1</cell>
                            <cell style="text-align:right;">265,385</cell>
                            <cell style="text-align:right;">12.56%</cell>
                            <cell style="text-align:right;">1,890,549</cell>
                            <cell style="text-align:right;">20.50%</cell>
                        </row>
                        <row>
                            <cell>2-10</cell>
                            <cell style="text-align:right;">175,788</cell>
                            <cell style="text-align:right;">8.32%</cell>
                            <cell style="text-align:right;">1,160,057</cell>
                            <cell style="text-align:right;">12.58%</cell>
                        </row>
                        <row>
                            <cell>&gt;10</cell>
                            <cell style="text-align:right;">7,982</cell>
                            <cell style="text-align:right;">0.38%</cell>
                            <cell style="text-align:right;">64,082</cell>
                            <cell style="text-align:right;">0.69%</cell>
                        </row>
                        <row>
                            <cell>Total</cell>
                            <cell style="text-align:right;">2,112,910</cell>
                            <cell style="text-align:right;">100.00%</cell>
                            <cell style="text-align:right;">9,223,736</cell>
                            <cell style="text-align:right;">100.00%</cell>
                        </row>
                        <row role="label" style="border-top:0.5px solid #333333;">
                            <cell cols="5">No. of retweets</cell>
                        </row>
                        <row role="label">
                            <cell rows="2"/>
                            <cell style="border:0.5px solid #333333;" cols="2">Corporate users</cell>
                            <cell style="border:0.5px solid #333333;" cols="2">Private users</cell>
                        </row>
                        <row role="label" style="border-bottom:0.5px solid #333333;">
                            <cell style="border:0.5px solid #333333;">No. of tweets</cell>
                            <cell style="border:0.5px solid #333333;">%</cell>
                            <cell style="border:0.5px solid #333333;">No. of tweets</cell>
                            <cell style="border:0.5px solid #333333;">%</cell>
                        </row>
                        <row>
                            <cell>0</cell>
                            <cell style="text-align:right;">1,754,988</cell>
                            <cell style="text-align:right;">83.06%</cell>
                            <cell style="text-align:right;">8,414,713</cell>
                            <cell style="text-align:right;">91.23%</cell>
                        </row>
                        <row>
                            <cell>1</cell>
                            <cell style="text-align:right;">219,698</cell>
                            <cell style="text-align:right;">10.40%</cell>
                            <cell style="text-align:right;">490,346</cell>
                            <cell style="text-align:right;">5.32%</cell>
                        </row>
                        <row>
                            <cell>2-10</cell>
                            <cell style="text-align:right;">134,184</cell>
                            <cell style="text-align:right;">6.35%</cell>
                            <cell style="text-align:right;">300,319</cell>
                            <cell style="text-align:right;">3.26%</cell>
                        </row>
                        <row>
                            <cell>&gt;10</cell>
                            <cell style="text-align:right;">4,040</cell>
                            <cell style="text-align:right;">0.19%</cell>
                            <cell style="text-align:right;">18,358</cell>
                            <cell style="text-align:right;">0.19%</cell>
                        </row>
                        <row>
                            <cell>Total</cell>
                            <cell style="text-align:right;">2,112,910</cell>
                            <cell style="text-align:right;">100.00%</cell>
                            <cell style="text-align:right;">9,223,736</cell>
                            <cell style="text-align:right;">100.00%</cell>
                        </row>
                    </table>
                    <figure>
                        <head>Figures 3 and 4: The most liked (left) and the most retweeted (right)
                            tweet posted by corporate users in the Janes-Tweet corpus.</head>
                        <graphic url="image3.png" height="300px"/>
                        <graphic url="image4.png" height="300px"/>
                    </figure>
                    <table rend="table-scroll">
                        <head>Table 5: Use of hashtags, emoji, hyperlinks and mentions by corporate and
                            private users in the Janes-Tweet corpus.</head>
                        <row role="label" style="border-top:0.5px solid #333333;">
                            <cell cols="4">Hashtags</cell>
                        </row>
                        <row role="label" style="border-bottom:0.5px solid #333333;">
                            <cell/>
                            <cell>Abs. freq.</cell>
                            <cell>Per million</cell>
                            <cell>Per tweet</cell>
                        </row>
                        <row>
                            <cell>Corporate</cell>
                            <cell style="text-align:right;">922,504</cell>
                            <cell style="text-align:right;">30,746.9</cell>
                            <cell style="text-align:right;">0.44</cell>
                        </row>
                        <row>
                            <cell>Private</cell>
                            <cell style="text-align:right;">2,241,693</cell>
                            <cell style="text-align:right;">17,190.8</cell>
                            <cell style="text-align:right;">0.24</cell>
                        </row>
                        <row role="label" style="border-top:0.5px solid #333333;">
                            <cell cols="4">Emoji</cell>
                        </row>
                        <row role="label" style="border-bottom:0.5px solid #333333;">
                            <cell/>
                            <cell>Abs. freq.</cell>
                            <cell>Per million</cell>
                            <cell>Per tweet</cell>
                        </row>
                        <row>
                            <cell>Corporate</cell>
                            <cell style="text-align:right;">1,285,696</cell>
                            <cell style="text-align:right;">42,852.0</cell>
                            <cell style="text-align:right;">0.61</cell>
                        </row>
                        <row>
                            <cell>Private</cell>
                            <cell style="text-align:right;">12,061,885</cell>
                            <cell style="text-align:right;">92,498.3</cell>
                            <cell style="text-align:right;">1.31</cell>
                        </row>
                        <row role="label" style="border-top:0.5px solid #333333;">
                            <cell cols="4">Hyperlinks</cell>
                        </row>
                        <row role="label" style="border-bottom:0.5px solid #333333;">
                            <cell/>
                            <cell>Abs. freq.</cell>
                            <cell>Per million</cell>
                            <cell>Per tweet</cell>
                        </row>
                        <row>
                            <cell>Corporate</cell>
                            <cell style="text-align:right;">1,989,643</cell>
                            <cell style="text-align:right;">66,314.4</cell>
                            <cell style="text-align:right;">0.94</cell>
                        </row>
                        <row>
                            <cell>Private</cell>
                            <cell style="text-align:right;">2,583,651</cell>
                            <cell style="text-align:right;">19,813.1</cell>
                            <cell style="text-align:right;">0.28</cell>
                        </row>
                        <row role="label" style="border-top:0.5px solid #333333;">
                            <cell cols="4">Mentions</cell>
                        </row>
                        <row role="label" style="border-bottom:0.5px solid #333333;">
                            <cell/>
                            <cell>Abs. freq.</cell>
                            <cell>Per million</cell>
                            <cell>Per tweet</cell>
                        </row>
                        <row>
                            <cell>Corporate</cell>
                            <cell style="text-align:right;">659,211</cell>
                            <cell style="text-align:right;">21,971.4</cell>
                            <cell style="text-align:right;">0.31</cell>
                        </row>
                        <row>
                            <cell>Private</cell>
                            <cell style="text-align:right;">9,216,857</cell>
                            <cell style="text-align:right;">57,460.2</cell>
                            <cell style="text-align:right;">1.00</cell>
                        </row>
                    </table>
                    <p>
                        <hi rend="bold">Retweets.</hi> Retweeting results show a different picture
                        where a much greater share of corporate tweets have at least one retweet
                        (17%) in comparison to private tweets (8%), suggesting a higher informative
                        value of corporate tweets for a wider audience. Interestingly, when
                        considering very frequently retweeted posts, no difference between the two
                        account types has been observed.</p>
                    <p>
                        <hi rend="bold">Use of hashtags. </hi>Relatively
                        speaking, corporate accounts use hashtags almost twice as often as private
                        accounts. On average, almost every second corporate tweet contains a
                        hashtag, which holds for only every fourth private tweet. As presented in
                        Table 5, sport is the predominant topic of the 10 most frequent hashtags
                        used by corporate users which is very similar to private users.
                        Interestingly, half of the 10 most frequently used hashtags are shared
                        (sport, news, Ljubljana). Among the 10 corporate users with the highest
                        relative frequency of hashtag use we can find less formal magazines and
                        companies. Therefore, for a more detailed analysis of corporate
                        communication it would be interesting to further divide corporate users into
                        different groups: media (journals and magazines), companies, state
                        institutions and non-governmental organizations. We plan to include this in
                        our future studies.</p>
                    <p>
                        <hi rend="bold">Use of emoticons and emojis.</hi><note place="foot" xml:id="ftn4" n="2"> Emoticons (e.g. ;)) are combinations of standard
                            typographical characters used for expressing emotions. Emojis are
                            pictograms (e.g. &#127874;)
                            which include emotions as well as a broad range of other topics and
                            their usage and interpretation depend on the individual.</note> The
                        usage of emoticons and emojis is opposite to hashtags, as emojis are,
                        relatively speaking, more than twice as common in posts by private users who
                        use 1.3 emojis or emoticons per tweet on average while occurring only in
                        every second corporate tweet which indicates greater degree of formality in
                        corporate communication on Twitter. Among the 10 corporate accounts the
                        relative frequency of emojis and emoticons, we mainly identified resellers
                        of fashion items.</p>
                    <p>As presented in Table 6, all of the most frequently used emojis or emoticons
                        are positive which again indicates a positive tone in PR communication.
                        However, it is interesting that only 2 emojis appear on the top 10 list for
                        corporate users while the rest are emoticons. This could be a sign of more
                        conservative communication strategies used by corporate users given that
                        emojis are a much more recent phenomenon, but this could also be a
                        consequence of corporate users more frequently tweeting from their computers
                        rather than smart phones which better support the use of emojis.</p>
                    <table rend="table-scroll">
                        <head>Table 6: Ten most frequent hashtags in corporate and private tweets.</head>
                        <row role="label">
                            <cell style="border:0.5px solid #333333;" cols="2">Corporate users</cell>
                            <cell style="border:0.5px solid #333333;" cols="2">Private users</cell>
                        </row>
                        <row role="label">
                            <cell style="border:0.5px solid #333333;">Hashtag</cell>
                            <cell style="border:0.5px solid #333333;">Frequency</cell>
                            <cell style="border:0.5px solid #333333;">Hashtag</cell>
                            <cell style="border:0.5px solid #333333;">Frequency</cell>
                        </row>
                        <row>
                            <cell><hi rend="bold">#plts</hi></cell>
                            <cell style="text-align:right;">18,03</cell>
                            <cell><hi rend="bold">#plts</hi></cell>
                            <cell style="text-align:right;">26,370</cell>
                        </row>
                        <row>
                            <cell><hi rend="bold">#slonews</hi></cell>
                            <cell style="text-align:right;">18,247</cell>
                            <cell><hi rend="bold">#slonews</hi></cell>
                            <cell style="text-align:right;">18,270</cell>
                        </row>
                        <row>
                            <cell><hi rend="bold">#PLTS</hi></cell>
                            <cell style="text-align:right;">9,620</cell>
                            <cell><hi rend="bold">#junaki</hi></cell>
                            <cell style="text-align:right;">18,167</cell>
                        </row>
                        <row>
                            <cell><hi rend="bold">#Ljubljana</hi></cell>
                            <cell style="text-align:right;">5,724</cell>
                            <cell>#slochi</cell>
                            <cell style="text-align:right;">13,195</cell>
                        </row>
                        <row>
                            <cell>#izvršba</cell>
                            <cell style="text-align:right;">5,167</cell>
                            <cell><hi rend="bold">#PLTS</hi></cell>
                            <cell style="text-align:right;">10,943</cell>
                        </row>
                        <row>
                            <cell>#NKDomzale</cell>
                            <cell style="text-align:right;">4,437</cell>
                            <cell>#Slovenia</cell>
                            <cell style="text-align:right;">10,780</cell>
                        </row>
                        <row>
                            <cell>#olimpija</cell>
                            <cell style="text-align:right;">4,176</cell>
                            <cell><hi rend="bold">#Ljubljana</hi></cell>
                            <cell style="text-align:right;">10,141</cell>
                        </row>
                        <row>
                            <cell>#rokomet</cell>
                            <cell style="text-align:right;">4,143</cell>
                            <cell>#radiobattleSI</cell>
                            <cell style="text-align:right;">9,184</cell>
                        </row>
                        <row>
                            <cell><hi rend="bold">#junaki</hi></cell>
                            <cell style="text-align:right;">3,941</cell>
                            <cell>#ligaprvakov</cell>
                            <cell style="text-align:right;">9,091</cell>
                        </row>
                        <row>
                            <cell>#skupajdovrha</cell>
                            <cell style="text-align:right;">3,864</cell>
                            <cell>#sp14si</cell>
                            <cell style="text-align:right;">8,351</cell>
                        </row>
                    </table>
                    <table rend="table-scroll">
                        <head>Table 7: Ten most frequent emoticons and emojis in corporate and private
                            tweets and the ten corporate accounts with the highest relative frequency of
                            emoticons and emojis.</head>
                        <row role="label">
                            <cell>Emoji</cell>
                            <cell>Frequency</cell>
                            <cell>User</cell>
                            <cell>Frequency</cell>
                            <cell>Rel. freq<note place="foot" xml:id="ftn5" n="3">
                                    Relative frequency is the average frequency of the phenomenon in
                                    one million tokens.</note></cell>
                        </row>
                        <row>
                            <cell>:)</cell>
                            <cell style="text-align:right;">114,602</cell>
                            <cell>RecycleMan</cell>
                            <cell style="text-align:right;">530</cell>
                            <cell style="text-align:right;">12.711,5</cell>
                        </row>
                        <row>
                            <cell>;)</cell>
                            <cell style="text-align:right;">55,763</cell>
                            <cell>JennParisBags</cell>
                            <cell style="text-align:right;">188</cell>
                            <cell style="text-align:right;">11.522,1</cell>
                        </row>
                        <row>
                            <cell>:D</cell>
                            <cell style="text-align:right;">17,715</cell>
                            <cell>EtiVelikonja</cell>
                            <cell style="text-align:right;">160</cell>
                            <cell style="text-align:right;">10.409,8</cell>
                        </row>
                        <row>
                            <cell>&amp;lt;3</cell>
                            <cell style="text-align:right;">13,688</cell>
                            <cell>ApartmaNet</cell>
                            <cell style="text-align:right;">184</cell>
                            <cell style="text-align:right;">10.104,9</cell>
                        </row>
                        <row>
                            <cell>:-)</cell>
                            <cell style="text-align:right;">9,672</cell>
                            <cell>TRENDtrgovina</cell>
                            <cell style="text-align:right;">436</cell>
                            <cell style="text-align:right;">10.049,3</cell>
                        </row>
                        <row>
                            <cell>;-)</cell>
                            <cell style="text-align:right;">4,926</cell>
                            <cell>Pawla40</cell>
                            <cell style="text-align:right;">228</cell>
                            <cell style="text-align:right;">9.720,0</cell>
                        </row>
                        <row>
                            <cell>:))</cell>
                            <cell style="text-align:right;">4,680</cell>
                            <cell>iPlacesi</cell>
                            <cell style="text-align:right;">125</cell>
                            <cell style="text-align:right;">8.860,0</cell>
                        </row>
                        <row>
                            <cell>❤</cell>
                            <cell style="text-align:right;">3,679</cell>
                            <cell>bozicluka</cell>
                            <cell style="text-align:right;">92</cell>
                            <cell style="text-align:right;">8.290,2</cell>
                        </row>
                        <row>
                            <cell>:P</cell>
                            <cell style="text-align:right;">3,558</cell>
                            <cell>matejgaber22</cell>
                            <cell style="text-align:right;">99</cell>
                            <cell style="text-align:right;">7.222,6</cell>
                        </row>
                        <row>
                            <cell>&#128521;</cell>
                            <cell style="text-align:right;">3,436</cell>
                            <cell>Modniovitki</cell>
                            <cell style="text-align:right;">424</cell>
                            <cell style="text-align:right;">7.010,9</cell>
                        </row>
                    </table>
                    <p>
                        <hi rend="bold">Use of hyperlinks.</hi> Great
                        differences between private and corporate users can be observed in their use
                        of hyperlinks in tweets. Relatively speaking, corporate tweets contain more
                        than three times the number of hyperlinks in comparison to private tweets.
                        On average, corporate users add a hyperlink to nearly each tweet they post,
                        while private users include it only in every fourth tweet. This corresponds
                        to the findings of our preliminary analysis that tweets are often only
                        compressed press releases leading to a complete message in the form of a
                        hyperlink.</p>
                    <p>
                        <hi rend="bold">Mentions of other users.</hi> Big
                        differences between private and corporate users are observed in the rate and
                        type of other user accounts mentions. Relatively speaking, mentions are more
                        than twice as frequent in private tweets as they are in corporate tweets. On
                        average, private users mention other users in every tweet, whereas corporate
                        users use this option only in every third message. This is not surprising
                        because the main objective of PR tweets is self-presentation, which is why
                        referencing others is less needed. Among the 10 most frequently mentioned
                        accounts in corporate tweets are mainly media, political
                        institutions/parties/individual politicians and sport organizations, while
                        in private tweets we find social media influencers, two journalists and a
                        politician. Both lists have only two mentions in common, i.e. YouTube and
                        Janez Janša, one of the oldest and best known Slovenian politicians.</p>
                    <table rend="table-scroll">
                        <head>Table 8: Ten most frequently mentioned accounts in the tweets posted by
                            corporate and by private users.</head>
                        <row role="label">
                            <cell style="border:0.5px solid #333333;" cols="2">Corporate users</cell>
                            <cell style="border:0.5px solid #333333;" cols="3">Private users</cell>
                        </row>
                        <row role="label">
                            <cell style="border:0.5px solid #333333;">Mention</cell>
                            <cell style="border:0.5px solid #333333;">Frequency</cell>
                            <cell style="border:0.5px solid #333333;">Mention</cell>
                            <cell style="border:0.5px solid #333333;">Frequency</cell>
                        </row>
                        <row>
                            <cell><hi rend="bold">@YouTube</hi></cell>
                            <cell style="text-align:right;">8,325</cell>
                            <cell>@petrasovdat</cell>
                            <cell style="text-align:right;">91,328</cell>
                        </row>
                        <row>
                            <cell>@Nova24TV</cell>
                            <cell style="text-align:right;">6,903</cell>
                            <cell><hi rend="bold">@YouTube</hi></cell>
                            <cell style="text-align:right;">71,859</cell>
                        </row>
                        <row>
                            <cell>@Val202</cell>
                            <cell style="text-align:right;">3,992</cell>
                            <cell>@MarkoSket</cell>
                            <cell style="text-align:right;">57,333</cell>
                        </row>
                        <row>
                            <cell>@rtvslo</cell>
                            <cell style="text-align:right;">3,866</cell>
                            <cell><hi rend="bold">@JJansaSDS</hi></cell>
                            <cell style="text-align:right;">53,482</cell>
                        </row>
                        <row>
                            <cell>@kzssi</cell>
                            <cell style="text-align:right;">3,736</cell>
                            <cell>@lucijausaj</cell>
                            <cell style="text-align:right;">51,391</cell>
                        </row>
                        <row>
                            <cell>@unionolimpija</cell>
                            <cell style="text-align:right;">3,616</cell>
                            <cell>@leaathenatabako</cell>
                            <cell style="text-align:right;">44,453</cell>
                        </row>
                        <row>
                            <cell><hi rend="bold">@JJansaSDS</hi></cell>
                            <cell style="text-align:right;">3,464</cell>
                            <cell>@petrajansa</cell>
                            <cell style="text-align:right;">44,102</cell>
                        </row>
                        <row>
                            <cell>@radioPrvi</cell>
                            <cell style="text-align:right;">3,128</cell>
                            <cell>@savicdomen</cell>
                            <cell style="text-align:right;">43,394</cell>
                        </row>
                        <row>
                            <cell>@vladaRS</cell>
                            <cell style="text-align:right;">2,764</cell>
                            <cell>@darkob</cell>
                            <cell style="text-align:right;">42,363</cell>
                        </row>
                        <row>
                            <cell>@nkmaribor</cell>
                            <cell style="text-align:right;">2,758</cell>
                            <cell>@zzTurk</cell>
                            <cell style="text-align:right;">40,534</cell>
                        </row>
                    </table>
                </div>
                <div>
                    <head>Language Analysis</head>
                    <p>
                        <hi rend="bold">Language of tweets.</hi> Corporate
                        users almost exclusively post messages in Slovene (93%), which is
                        considerably different from private users whose share of tweets in a foreign
                        language is twice as large. Among the foreign languages used in tweets of
                        corporate users, English prevails (5%). This corresponds to our preliminary
                        findings that the main goal of Slovene corporate Twitter users is to address
                        their Slovene audience through formal communication for business or
                        informative purposes. The only exception are the accounts of Slovene
                        Embassies around the world often posting in their local language (e.g. in
                        French), as well as the accounts of the Ministry of Foreign Affairs, the
                        president and the prime minister who occasionally use English tweets to
                        inform the international community about major events (e.g. arbitration). </p>
                    <table rend="table-scroll">
                        <head>Table 9: Language use in the tweets posted by corporate and private
                            users.</head>
                        <row role="label">
                            <cell style="border:0.5px solid #333333;" rows="2">Language</cell>
                            <cell style="border:0.5px solid #333333;" cols="2">Corporate</cell>
                            <cell style="border:0.5px solid #333333;" cols="2">Private</cell>
                        </row>
                        <row role="label">
                            <cell style="border:0.5px solid #333333;">No. of tweets</cell>
                            <cell style="border:0.5px solid #333333;">%</cell>
                            <cell style="border:0.5px solid #333333;">No. of tweets</cell>
                            <cell style="border:0.5px solid #333333;">%</cell>
                        </row>
                        <row>
                            <cell>Slovene</cell>
                            <cell style="text-align:right;">1,973,677</cell>
                            <cell style="text-align:right;">93.41%</cell>
                            <cell style="text-align:right;">8,074,681</cell>
                            <cell style="text-align:right;">87.54%</cell>
                        </row>
                        <row>
                            <cell>English</cell>
                            <cell style="text-align:right;">104,955</cell>
                            <cell style="text-align:right;">4.97%</cell>
                            <cell style="text-align:right;">983,141</cell>
                            <cell style="text-align:right;">10.66%</cell>
                        </row>
                        <row>
                            <cell>Bosnian/Croatian/Serbian</cell>
                            <cell style="text-align:right;">16,058</cell>
                            <cell style="text-align:right;">0.76%</cell>
                            <cell style="text-align:right;">57,017</cell>
                            <cell style="text-align:right;">0.62%</cell>
                        </row>
                        <row>
                            <cell>Other</cell>
                            <cell style="text-align:right;">18,220</cell>
                            <cell style="text-align:right;">0.86%</cell>
                            <cell style="text-align:right;">108,897</cell>
                            <cell style="text-align:right;">1.18%</cell>
                        </row>
                        <row>
                            <cell>Total</cell>
                            <cell style="text-align:right;">2,112,910</cell>
                            <cell style="text-align:right;">100.00%</cell>
                            <cell style="text-align:right;">9,223,736</cell>
                            <cell style="text-align:right;">100.00%</cell>
                        </row>
                    </table>
                    <p>
                        <hi rend="bold">Sentiment of tweets.</hi> Every tweet
                        in the corpus is annotated with a sentiment label (see <ref target="#Erjavec.2018">Erjavec et al. 2018</ref>).
                        Half of all corporate tweets have positive sentiment, a third has neutral
                        sentiment and 17% of the tweets have negative sentiment. This greatly
                        differs from private tweets, half of which are neutral, 27% negative and
                        only a quarter positive. This is another indication of the PR nature of
                        corporate tweets which try to convey a positive corporate image, attract
                        customers, sell products, etc.</p>
                    <table rend="table-scroll">
                        <head>Table 10: Sentiment of tweets posted by corporate and private users.</head>
                        <row role="label">
                            <cell style="border:0.5px solid #333333;" rows="2">sentiment</cell>
                            <cell style="border:0.5px solid #333333;" cols="2">corporate</cell>
                            <cell style="border:0.5px solid #333333;" cols="2">private</cell>
                        </row>
                        <row role="label">
                            <cell style="border:0.5px solid #333333;">no. of tweets</cell>
                            <cell style="border:0.5px solid #333333;">%</cell>
                            <cell style="border:0.5px solid #333333;">no. of tweets</cell>
                            <cell style="border:0.5px solid #333333;">%</cell>
                        </row>
                        <row>
                            <cell>positive</cell>
                            <cell style="text-align:right;">1,024,238</cell>
                            <cell style="text-align:right;">48.48%</cell>
                            <cell style="text-align:right;">2,320,841</cell>
                            <cell style="text-align:right;">25.16%</cell>
                        </row>
                        <row>
                            <cell>neutral</cell>
                            <cell style="text-align:right;">729,811</cell>
                            <cell style="text-align:right;">34.54%</cell>
                            <cell style="text-align:right;">4,411,516</cell>
                            <cell style="text-align:right;">47.83%</cell>
                        </row>
                        <row>
                            <cell>negative</cell>
                            <cell style="text-align:right;">358,861</cell>
                            <cell style="text-align:right;">16.98%</cell>
                            <cell style="text-align:right;">2,491,379</cell>
                            <cell style="text-align:right;">27.01%</cell>
                        </row>
                        <row>
                            <cell>total</cell>
                            <cell style="text-align:right;">2,112,910</cell>
                            <cell style="text-align:right;">100.00%</cell>
                            <cell style="text-align:right;">9,223,736</cell>
                            <cell style="text-align:right;">100.00%</cell>
                        </row>
                    </table>
                    <p>
                        <hi rend="bold">Language standardness.</hi> Tweets by
                        corporate users mainly contain standard Slovene (80%) and highly nonstandard
                        content is only rarely present (3%). Almost the opposite is true of private
                        users. Less than half of their tweets are written in standard Slovene and
                        the share of tweets containing highly nonstandard Slovene is more than four
                        times greater in comparison to corporate users. Some exceptions can be found
                        among the accounts of public personalities (e.g. stand-up comics, radio
                        presenters, musicians) who often purposefully tweet in nonstandard Slovene
                        because informal communication is a major part of their corporate image.</p>
                    <table rend="table-scroll">
                        <head>Table 11: Language standardness level in the tweets posted by corporate and
                            private users.</head>
                        <row role="label">
                            <cell style="border:0.5px solid #333333;" rows="2">Standardness</cell>
                            <cell style="border:0.5px solid #333333;" cols="2">Corporate</cell>
                            <cell style="border:0.5px solid #333333;" cols="2">Private</cell>
                        </row>
                        <row role="label">
                            <cell style="border:0.5px solid #333333;">No. of tweets</cell>
                            <cell style="border:0.5px solid #333333;">%</cell>
                            <cell style="border:0.5px solid #333333;">Sentiment</cell>
                            <cell style="border:0.5px solid #333333;">No. of tweets</cell>
                        </row>
                        <row>
                            <cell>L1</cell>
                            <cell style="text-align:right;">1,688,244</cell>
                            <cell style="text-align:right;">79.90%</cell>
                            <cell style="text-align:right;">4,515,310</cell>
                            <cell style="text-align:right;">48.95%</cell>
                        </row>
                        <row>
                            <cell>L2</cell>
                            <cell style="text-align:right;">353,397</cell>
                            <cell style="text-align:right;">16.73%</cell>
                            <cell style="text-align:right;">3,489,743</cell>
                            <cell style="text-align:right;">37.83%</cell>
                        </row>
                        <row>
                            <cell>L3</cell>
                            <cell style="text-align:right;">71,269</cell>
                            <cell style="text-align:right;">3.37%</cell>
                            <cell style="text-align:right;">1,218,683</cell>
                            <cell style="text-align:right;">13.21%</cell>
                        </row>
                        <row>
                            <cell></cell>
                            <cell style="text-align:right;">2,112,910</cell>
                            <cell style="text-align:right;">100.00%</cell>
                            <cell style="text-align:right;">9,223,736</cell>
                            <cell style="text-align:right;">100.00%</cell>
                        </row>
                    </table>
                    <table rend="table-scroll">
                        <head>Table 12: Comparison of the language used in corporate and private tweets
                            according to part of speech.</head>
                        <row role="label">
                            <cell>Part of speech</cell>
                            <cell>Corporate (per million)</cell>
                            <cell>Private (per million)</cell>
                            <cell>Ratio<note place="foot" xml:id="ftn6" n="4"> Ratio
                                    between the frequency in corporate and in private
                                tweets.</note></cell>
                        </row>
                        <row>
                            <cell>Proper nouns</cell>
                            <cell style="text-align:right;">66,738.4</cell>
                            <cell style="text-align:right;">33,507.8</cell>
                            <cell style="text-align:right;">1.99</cell>
                        </row>
                        <row>
                            <cell>Numerals</cell>
                            <cell style="text-align:right;">30,564.9</cell>
                            <cell style="text-align:right;">16,109.7</cell>
                            <cell style="text-align:right;">1.90</cell>
                        </row>
                        <row>
                            <cell>Conjunctions</cell>
                            <cell style="text-align:right;">54,381.1</cell>
                            <cell style="text-align:right;">33,302.1</cell>
                            <cell style="text-align:right;">1.63</cell>
                        </row>
                        <row>
                            <cell>Prepositions</cell>
                            <cell style="text-align:right;">86,947.2</cell>
                            <cell style="text-align:right;">54,549.6</cell>
                            <cell style="text-align:right;">1.59</cell>
                        </row>
                        <row>
                            <cell>Adjectives</cell>
                            <cell style="text-align:right;">76,889.9</cell>
                            <cell style="text-align:right;">48,254.8</cell>
                            <cell style="text-align:right;">1.59</cell>
                        </row>
                        <row>
                            <cell>Common nouns</cell>
                            <cell style="text-align:right;">186,446.6</cell>
                            <cell style="text-align:right;">127,056.0</cell>
                            <cell style="text-align:right;">1.47</cell>
                        </row>
                        <row>
                            <cell>Abbreviations</cell>
                            <cell style="text-align:right;">3,826.0</cell>
                            <cell style="text-align:right;">3,458.9</cell>
                            <cell style="text-align:right;">1.11</cell>
                        </row>
                        <row>
                            <cell>Punctuation</cell>
                            <cell style="text-align:right;">143,234.6</cell>
                            <cell style="text-align:right;">158,188.2</cell>
                            <cell style="text-align:right;">0.91</cell>
                        </row>
                        <row>
                            <cell>Main verbs</cell>
                            <cell style="text-align:right;">62,631.9</cell>
                            <cell style="text-align:right;">75,795.7</cell>
                            <cell style="text-align:right;">0.83</cell>
                        </row>
                        <row>
                            <cell>Auxiliary verbs</cell>
                            <cell style="text-align:right;">36,974.7</cell>
                            <cell style="text-align:right;">52,968.0</cell>
                            <cell style="text-align:right;">0.70</cell>
                        </row>
                        <row>
                            <cell>Adverbs</cell>
                            <cell style="text-align:right;">38,192.1</cell>
                            <cell style="text-align:right;">55,483.1</cell>
                            <cell style="text-align:right;">0.69</cell>
                        </row>
                        <row>
                            <cell>Pronouns</cell>
                            <cell style="text-align:right;">39,118.2</cell>
                            <cell style="text-align:right;">62,678.8</cell>
                            <cell style="text-align:right;">0.62</cell>
                        </row>
                        <row>
                            <cell>Particles</cell>
                            <cell style="text-align:right;">19,816.6</cell>
                            <cell style="text-align:right;">35,540.7</cell>
                            <cell style="text-align:right;">0.56</cell>
                        </row>
                        <row>
                            <cell>Interjections</cell>
                            <cell style="text-align:right;">1,740.9</cell>
                            <cell style="text-align:right;">6,194.5</cell>
                            <cell style="text-align:right;">0.28</cell>
                        </row>
                    </table>
                    <p>
                        <hi rend="bold">Orthography.</hi> Great differences are detected regarding
                        the use of abbreviations: corporate tweets mainly contain standard
                        abbreviations of academic or other titles (<hi rend="italic">dr., mag., d.
                            o. o.</hi>) and common abbreviations (<hi rend="italic">št., oz.,
                            min.</hi>), while in private tweets we find nonstandard abbreviations
                            (<hi rend="italic">tw</hi>), often without full stop (<hi rend="italic">slo, lj, min</hi>).
                        Some differences can be also observed in the use of
                        punctuation. In corporate accounts, a bigger range of classic punctuation
                        marks is used according to the orthographic norm. Tweets by private users
                        are characterized by frequent repetitions of the same punctuation mark to
                        give the message an emotional charge. Much more frequent is also the use of
                        social-media specific symbols (<hi rend="italic">#, @, *</hi>).</p>
                    <p>
                        <hi rend="bold">Parts of speech.</hi> The analysis of
                        the parts of speech in the language of corporate tweets offers an insight
                        into communication purposes of corporate accounts. Relatively speaking,
                        there are almost twice as many proper nouns and numerals in corporate tweets
                        than in private ones. Much more frequent are also conjunctions,
                        prepositions, adjectives and common nouns. As shown in Table 10,
                        interjections are considerably more often present in private accounts (3.5
                        times more). The same is true for particles (almost 2 times more), pronouns
                        and adverbs. On the one hand this confirms a greater formality of corporate
                        users and reflects a more direct and personal approach of private users. On
                        the other hand this also reflects different communicative functions of
                        Twitter: informative for corporate and conversational for private accounts.
                        Furthermore, the informative, as well as the influencing function to some
                        extent, are also confirmed by the detailed analysis of individual parts of
                        speech presented below.</p>
                    <p>
                        <hi rend="bold">The noun. </hi>Common nouns are 1.5
                        times more common in corporate tweets than in private ones, but the matching
                        rate of the first 20 common nouns that are most frequently used is
                        surprisingly high (70%): <hi rend="italic">dan/day, leto/year, tekma/race,
                            ura/hour, mesto/place, teden/week, čas/time, hvala/thank you,
                            svet/world, delo/work, človek/human, konec/end, otrok/child,
                            država/country</hi>. Among the 20 most frequent nouns, the following are
                        specific to corporate tweets: <hi rend="italic">video/video, foto/photo,
                            zmaga/victory, novica/news, cena/price, sezona/season</hi>. Proper nouns
                        are twice as common in corporate tweets than in the private ones and the
                        matching rate of the 20 most frequent nouns is 40%: <hi rend="italic">Slovenija/Slovenia, Ljubljana, Maribor, EU, Slovenc/Slovene,
                            Evropa/Europe, ZDA/USA, Cerar, Janša</hi>. Among the 20 most frequent
                        nouns, the following proper nouns are corporate tweets: <hi rend="italic">Olimpija, Koper, Peter, Gorica, Janez, Domžale, Luka, Tina,
                        Marko</hi>.</p>
                    <p>In corporate tweets a higher level of formality of expression has been
                        detected as both first and last names are indicated (private tweets mention
                        only the last name). Furthermore, we can observe greater diversity of places
                        and company names. An analysis of nominal pronouns returned predictable
                        results: corporate tweets contain plural pronouns (<hi rend="italic">nam/to
                            us, nas/us, vam</hi>/<hi rend="italic">to you</hi>), while in private
                        tweets we find singular forms of pronouns (<hi rend="italic">jaz/I, me/of
                            me, ti/to you, te/you</hi>). The reason for grammatical plurality lies
                        in the fact that authors of corporate tweets use formal communication
                        methods on behalf of their institution or company and formal form of
                        addressing.</p>
                    <p>
                        <hi rend="bold">The verb.</hi> The use of main verbs is
                        more common in private tweets. The matching rate of the 20 most frequent
                        verbs in private and corporate tweets is 60% (<hi rend="italic">imeti/have,
                            iti/go, morati/must, vedeti/know, videte/see, priti/come, dobiti/get,
                            začeti/begin, čakati/wait, dati/give, praviti/say, delati/work,
                            dobiti/get</hi>), but the difference lies in their motivation for
                        communication: corporate accounts mainly report on events and publish
                        statements, while private accounts describe personal activities and give
                        opinions. Among the 20 most frequent verbs, the following main verbs are
                        specific to corporate tweets: <hi rend="italic">želeti/wish,
                            preveriti/check, najti/find, iskati/search, prebrati/read,
                            gledati/watch, moči/able, hoteti/want, narediti/do</hi>.</p>
                    <p>
                        <hi rend="bold">The adjective.</hi> Adjectives are 1.5
                        times more frequently used in corporate than in private tweets and the
                        matching rate of the 20 most used adjectives is 50%: <hi rend="italic">nov/new, dober/good, slovenski/Slovenian, velik/big, lep/beautiful,
                            zadnji/last, mlad/young, star/old, pravi/real, super/super</hi>. Among
                        the 20 most frequent adjectives the following are specific to corporate
                        tweets: <hi rend="italic">vabljen/invited, današnji/today’s,
                            evropski/European, javen/public, spleten/web/based, svetoven/world/wide,
                            odličen/excellent, državen/national, visok/high, domač/domestic</hi>.
                        Positive adjectives are characteristic of corporate tweets (<hi rend="italic">nov/new, dober/good, velik/big, lep/beautiful</hi>) which
                        are also more formal than the adjectives characteristic of private tweets
                            (<hi rend="italic">vabljen/invited, odličen/excellent, visok/high</hi>
                        vs. <hi rend="italic">hud/badass, mali/little, sam/alone</hi>). Adjectival
                        as well as nominal pronouns are used in the first person plural form in
                        corporate tweets (<hi rend="italic">naše/our-Female, naši/our-Male</hi>)
                        when the goal is identification with the company or the institution and
                        integration into the communicative circle that connects the author of the
                        message on behalf of the institution with the recipient (<ref target="#Korošec.1998">Korošec 1998</ref>).</p>
                    <p>
                        <hi rend="bold">The particle.</hi> The difference
                        between formality and informality can also be observed through particles
                        which overlap in 80% of the cases. However, among the particles that are
                        present only in tweets of one user group, our analysis showed that formal
                        particles are distinctive for corporate tweets (<hi rend="italic">morda/maybe, predvsem/above all, sicer/though, skoraj/nearly</hi>) and
                        nonstandard and informal particles for private tweets <hi rend="italic">(tud
                            &lt; tudi/also; ze &lt; že/already, itak/off course, pač/well</hi>).</p>
                    <p>
                        <hi rend="bold">The interjection.</hi> As already
                        mentioned, the analysis of this part of speech showed most notable
                        differences. The matching rate of the 20 most common interjections in
                        corporate and private tweets is 55%: <hi rend="italic">bravo, hm, haha, uf,
                            o, ej, ah, ha, aha, aja, oh</hi>. Among the most frequent interjections
                        that are distinctive for one of the user groups are the following ones: <hi rend="italic">živjo, zdravo, hej, hehe, gooool, opa, ups, na, ojoj</hi>.
                        Interjections in corporate tweets are fewer in quantity as well as more
                        formal and salutatory (<hi rend="italic">zdravo, ups</hi>), while private
                        tweets often contain interjections in foreign language (<hi rend="italic">btw, lol</hi>) and swear words. </p>
                </div>
                <div>
                    <head>Keyword Analysis</head>
                    <p>This section highlights the results of the keyword analysis performed on
                        corporate tweets. In this paper, the keywords are understood as the words
                        which are unexpectedly more frequent in the tweets of corporate users
                        compared to the entire Janes-Tweet corpus as reference.</p>
                    <table rend="table-scroll">
                        <head>Table 13: List of 20 most key lemmas in corporate tweets according to
                            sentiment.</head>
                        <row role="label">
                            <cell>Negative</cell>
                            <cell>Keyness index</cell>
                            <cell>Positive</cell>
                            <cell>Keyness index</cell>
                            <cell>Neutral</cell>
                            <cell>Keyness index</cell>
                        </row>
                        <row>
                            <cell>oviran</cell>
                            <cell style="text-align:right;">22.2</cell>
                            <cell>čestitka</cell>
                            <cell style="text-align:right;">3.5</cell>
                            <cell>novice.si</cell>
                            <cell style="text-align:right;">10.1</cell>
                        </row>
                        <row>
                            <cell>trčenje</cell>
                            <cell style="text-align:right;">19.1</cell>
                            <cell>vabljen</cell>
                            <cell style="text-align:right;">3.5</cell>
                            <cell>zemljišče</cell>
                            <cell style="text-align:right;">8.7</cell>
                        </row>
                        <row>
                            <cell>trčiti</cell>
                            <cell style="text-align:right;">18.0</cell>
                            <cell>bravo</cell>
                            <cell style="text-align:right;">3.4</cell>
                            <cell>pivniški</cell>
                            <cell style="text-align:right;">8.3</cell>
                        </row>
                        <row>
                            <cell>priključek</cell>
                            <cell style="text-align:right;">15.4</cell>
                            <cell>album</cell>
                            <cell style="text-align:right;">3.4</cell>
                            <cell>ebel</cell>
                            <cell style="text-align:right;">8.3</cell>
                        </row>
                        <row>
                            <cell>evakuirati</cell>
                            <cell style="text-align:right;">15.3</cell>
                            <cell>beautiful</cell>
                            <cell style="text-align:right;">3.4</cell>
                            <cell>katarinin</cell>
                            <cell style="text-align:right;">8.1</cell>
                        </row>
                        <row>
                            <cell>ranjen</cell>
                            <cell style="text-align:right;">15.1</cell>
                            <cell>hvala</cell>
                            <cell style="text-align:right;">3.4</cell>
                            <cell>petv</cell>
                            <cell style="text-align:right;">8.0</cell>
                        </row>
                        <row>
                            <cell>poškodovan</cell>
                            <cell style="text-align:right;">15.0</cell>
                            <cell>posted</cell>
                            <cell style="text-align:right;">3.4</cell>
                            <cell>šloganje</cell>
                            <cell style="text-align:right;">7.9</cell>
                        </row>
                        <row>
                            <cell>razcep</cell>
                            <cell style="text-align:right;">14.9</cell>
                            <cell>photos</cell>
                            <cell style="text-align:right;">3.4</cell>
                            <cell>solaten</cell>
                            <cell style="text-align:right;">7.8</cell>
                        </row>
                        <row>
                            <cell>novicejutro.si</cell>
                            <cell style="text-align:right;">14.9</cell>
                            <cell>odličen</cell>
                            <cell style="text-align:right;">3.3</cell>
                            <cell>ugnati</cell>
                            <cell style="text-align:right;">7.8</cell>
                        </row>
                        <row>
                            <cell>osumljen</cell>
                            <cell style="text-align:right;">14.6</cell>
                            <cell>polepšati</cell>
                            <cell style="text-align:right;">3.3</cell>
                            <cell>pripravljalen</cell>
                            <cell style="text-align:right;">7.7</cell>
                        </row>
                        <row>
                            <cell>nesreča</cell>
                            <cell style="text-align:right;">14.5</cell>
                            <cell>odlično</cell>
                            <cell style="text-align:right;">3.3</cell>
                            <cell>koel</cell>
                            <cell style="text-align:right;">7.6</cell>
                        </row>
                        <row>
                            <cell>aretirati</cell>
                            <cell style="text-align:right;">14.3</cell>
                            <cell>prijeten</cell>
                            <cell style="text-align:right;">3.3</cell>
                            <cell>novinec</cell>
                            <cell style="text-align:right;">7.6</cell>
                        </row>
                        <row>
                            <cell>avtocesta</cell>
                            <cell style="text-align:right;">14.1</cell>
                            <cell>super</cell>
                            <cell style="text-align:right;">3.3</cell>
                            <cell>napovednik</cell>
                            <cell style="text-align:right;">7.4</cell>
                        </row>
                        <row>
                            <cell>neurje</cell>
                            <cell style="text-align:right;">14.1</cell>
                            <cell>čudovit</cell>
                            <cell style="text-align:right;">3.3</cell>
                            <cell>zoofa</cell>
                            <cell style="text-align:right;">7.3</cell>
                        </row>
                        <row>
                            <cell>strmoglaviti</cell>
                            <cell style="text-align:right;">13.9</cell>
                            <cell>čestitati</cell>
                            <cell style="text-align:right;">3.3</cell>
                            <cell>prerokovanje</cell>
                            <cell style="text-align:right;">7.3</cell>
                        </row>
                        <row>
                            <cell>osumljenec</cell>
                            <cell style="text-align:right;">13.1</cell>
                            <cell>srečno</cell>
                            <cell style="text-align:right;">3.3</cell>
                            <cell>poiesis</cell>
                            <cell style="text-align:right;">7.2</cell>
                        </row>
                        <row>
                            <cell>magnituda</cell>
                            <cell style="text-align:right;">13.1</cell>
                            <cell>facebook</cell>
                            <cell style="text-align:right;">3.3</cell>
                            <cell>apod</cell>
                            <cell style="text-align:right;">7.1</cell>
                        </row>
                        <row>
                            <cell>prometen</cell>
                            <cell style="text-align:right;">12.8</cell>
                            <cell>welcome</cell>
                            <cell style="text-align:right;">3.3</cell>
                            <cell>wt</cell>
                            <cell style="text-align:right;">7.1</cell>
                        </row>
                        <row>
                            <cell>ubit</cell>
                            <cell style="text-align:right;">12.8</cell>
                            <cell>summer</cell>
                            <cell style="text-align:right;">3.3</cell>
                            <cell>sklepen</cell>
                            <cell style="text-align:right;">6.9</cell>
                        </row>
                    </table>
                    <p>
                        <hi rend="bold">Sentiment.</hi> As shown in Table 13,
                        the highest keyness index is attributed to lexis from corporate tweets with
                        negative sentiment. Among those, all 20 top-ranking key lemmas are part of
                        media tweets that reference reports on crime and other accidents (e.g.,
                        <hi rend="italic">trčenje/collision, evakuirati/evacuate, ranjen/injured,
                            nesreča/accident</hi>). The 20 top-ranking keywords with positive
                        sentiment correspond to the definitions of positive PR communication (e.g.,
                            <hi rend="italic">čestitka/congratulations, vabljen/invited,
                            bravo/bravo, čudovit/wonderful, polepšati/make sbd’s (day)</hi>).
                        Adjectives and adverbs with highly positive meaning are also ranked high
                        (e.g., <hi rend="italic">lep/beautiful, odličen, odlično/fantastic,
                            prijeten/nice, super/super</hi>). Furthermore, the 20 top-ranking
                        keywords with neutral sentiment are part of the tweets containing media
                        reports (e.g., <hi rend="italic">novice.si/news.si, zemljišče/property,
                            napovednik/preview, sklepen/final</hi>) and denote events (e.g., <hi rend="italic">pivniški/beer, ebel/ebel, šloganje/card-reading,
                            prerokovanje/fortune-telling</hi>) or names (<hi rend="italic">katarinin, ebel, zoofa, apod</hi>). This list suggests that for a more
                        fine-grained analysis of corporate communication on Twitter it could be
                        useful to consider separating the tweets generated by media from those that
                        are created by companies or institutions.</p>
                    <table rend="table-scroll">
                        <head>Table 14: Comparison of key word forms in corporate tweets, written in
                            standard and non-standard language.</head>
                        <row role="label">
                            <cell>Standard tweets</cell>
                            <cell>Keyness index</cell>
                            <cell>Non-standard tweets</cell>
                            <cell>Keyness index</cell>
                        </row>
                        <row>
                            <cell>Izkl</cell>
                            <cell style="text-align:right;">6.4</cell>
                            <cell>Posetite</cell>
                            <cell style="text-align:right;">562.3</cell>
                        </row>
                        <row>
                            <cell>Novice.SI</cell>
                            <cell style="text-align:right;">6.4</cell>
                            <cell>potrazi</cell>
                            <cell style="text-align:right;">557.6</cell>
                        </row>
                        <row>
                            <cell>dražba</cell>
                            <cell style="text-align:right;">6.0</cell>
                            <cell>sjajan</cell>
                            <cell style="text-align:right;">553.5</cell>
                        </row>
                        <row>
                            <cell>[hyperlink]</cell>
                            <cell style="text-align:right;">5.9</cell>
                            <cell>Jeste</cell>
                            <cell style="text-align:right;">455.0</cell>
                        </row>
                        <row>
                            <cell>SiOL</cell>
                            <cell style="text-align:right;">5.8</cell>
                            <cell>tim</cell>
                            <cell style="text-align:right;">308.5</cell>
                        </row>
                        <row>
                            <cell>Petv</cell>
                            <cell style="text-align:right;">5.8</cell>
                            <cell>[hyperlink]</cell>
                            <cell style="text-align:right;">307.2</cell>
                        </row>
                        <row>
                            <cell>APOD</cell>
                            <cell style="text-align:right;">5.8</cell>
                            <cell>[hyperlink]</cell>
                            <cell style="text-align:right;">186.6</cell>
                        </row>
                        <row>
                            <cell>Moia</cell>
                            <cell style="text-align:right;">5.7</cell>
                            <cell>li</cell>
                            <cell style="text-align:right;">166.4</cell>
                        </row>
                        <row>
                            <cell>spletnem</cell>
                            <cell style="text-align:right;">5.7</cell>
                            <cell>koketo</cell>
                            <cell style="text-align:right;">145.9</cell>
                        </row>
                        <row>
                            <cell>Zurnal24</cell>
                            <cell style="text-align:right;">5.7</cell>
                            <cell>trombeto</cell>
                            <cell style="text-align:right;">143.3</cell>
                        </row>
                        <row>
                            <cell>ugodne</cell>
                            <cell style="text-align:right;">5.7</cell>
                            <cell>[hyperlink]</cell>
                            <cell style="text-align:right;">130.0</cell>
                        </row>
                        <row>
                            <cell>astronomska</cell>
                            <cell style="text-align:right;">5.7</cell>
                            <cell>belooranžnega</cell>
                            <cell style="text-align:right;">129.5</cell>
                        </row>
                        <row>
                            <cell>SMUČANJE</cell>
                            <cell style="text-align:right;">5.6</cell>
                            <cell>deejaytime</cell>
                            <cell style="text-align:right;">111.2</cell>
                        </row>
                        <row>
                            <cell>KOŠARKA</cell>
                            <cell style="text-align:right;">5.6</cell>
                            <cell>Živjo</cell>
                            <cell style="text-align:right;">111.0</cell>
                        </row>
                        <row>
                            <cell>oviran</cell>
                            <cell style="text-align:right;">5.6</cell>
                            <cell>Skupne</cell>
                            <cell style="text-align:right;">109.6</cell>
                        </row>
                        <row>
                            <cell>[hyperlink]</cell>
                            <cell style="text-align:right;">5.6</cell>
                            <cell>pritisne</cell>
                            <cell style="text-align:right;">92.8</cell>
                        </row>
                        <row>
                            <cell>ALPSKO</cell>
                            <cell style="text-align:right;">5.6</cell>
                            <cell>oglasiš</cell>
                            <cell style="text-align:right;">66.2</cell>
                        </row>
                        <row>
                            <cell>HOKEJ</cell>
                            <cell style="text-align:right;">5.6</cell>
                            <cell>[hyperlink]</cell>
                            <cell style="text-align:right;">65.9</cell>
                        </row>
                        <row>
                            <cell>zamudite</cell>
                            <cell style="text-align:right;">5.6</cell>
                            <cell>cheers</cell>
                            <cell style="text-align:right;">60.3</cell>
                        </row>
                        <row>
                            <cell>Preverite</cell>
                            <cell style="text-align:right;">5.5</cell>
                            <cell>hajskul</cell>
                            <cell style="text-align:right;">56.5</cell>
                        </row>
                        <row>
                            <cell>Nogometaši</cell>
                            <cell style="text-align:right;">5.5</cell>
                            <cell>[hyperlink]</cell>
                            <cell style="text-align:right;">49.6</cell>
                        </row>
                        <row>
                            <cell>TENIS</cell>
                            <cell style="text-align:right;">5.5</cell>
                            <cell>gnargnar</cell>
                            <cell style="text-align:right;">49.6</cell>
                        </row>
                        <row>
                            <cell>ciganskih</cell>
                            <cell style="text-align:right;">5.4</cell>
                            <cell>sporočimo</cell>
                            <cell style="text-align:right;">47.0</cell>
                        </row>
                        <row>
                            <cell>NOGOMET</cell>
                            <cell style="text-align:right;">5.4</cell>
                            <cell>najbrš</cell>
                            <cell style="text-align:right;">46.8</cell>
                        </row>
                        <row>
                            <cell>ROKOMET</cell>
                            <cell style="text-align:right;">5.4</cell>
                            <cell>pridte</cell>
                            <cell style="text-align:right;">45.3</cell>
                        </row>
                        <row>
                            <cell>[hyperlink]</cell>
                            <cell style="text-align:right;">5.4</cell>
                            <cell>javimo</cell>
                            <cell style="text-align:right;">41.9</cell>
                        </row>
                        <row>
                            <cell>Astrolife.si</cell>
                            <cell style="text-align:right;">5.4</cell>
                            <cell>Poslali</cell>
                            <cell style="text-align:right;">41.5</cell>
                        </row>
                        <row>
                            <cell>Izbrane</cell>
                            <cell style="text-align:right;">5.4</cell>
                            <cell>dm</cell>
                            <cell style="text-align:right;">41.2</cell>
                        </row>
                        <row>
                            <cell>Slovenske</cell>
                            <cell style="text-align:right;">5.4</cell>
                            <cell>javiš</cell>
                            <cell style="text-align:right;">41.2</cell>
                        </row>
                        <row>
                            <cell>SMUČARSKI</cell>
                            <cell style="text-align:right;">5.4</cell>
                            <cell>unc</cell>
                            <cell style="text-align:right;">41.0</cell>
                        </row>
                    </table>
                    <p>
                        <hi rend="bold">Standardness.</hi> A comparison of the
                        30 top-ranking key word forms (see Table 14) in corporate tweets written in
                        standard and nonstandard Slovene shows that users write in standard Slovene
                        when posting notifications and adds (e.g., <hi rend="italic">dražba/auction,
                            ugodne/good, zamudite/miss, preverite/check</hi>). Tweets written in
                        nonstandard Slovene have a similar communication purpose, but numerous
                        elements in foreign language and nonstandard spelling of Slovene words
                        indicate that authors of such messages want to establish a closer connection
                        with their target audience and make their offer more appealing to them (e.g.
                            <hi rend="italic">deejaytime/phoneticized spelling of DJ/time, hajskul –
                            phoneticized spelling of high school, najbrš – nonstandard for I guess,
                            pridte –nonstandard for come, dm – abbreviation for direct message,
                            javiš – nonstandard for answer</hi>).</p>
                    <table rend="table-scroll">
                        <head>Tabela 15: Comparison of key word forms in corporate tweets written by male
                            and female users.</head>
                        <row role="label">
                            <cell>Female</cell>
                            <cell>Keyness index</cell>
                            <cell>Male</cell>
                            <cell>Keyness index</cell>
                        </row>
                        <row>
                            <cell>foodwalks</cell>
                            <cell style="text-align:right;">7.7</cell>
                            <cell>Moia</cell>
                            <cell style="text-align:right;">41.7</cell>
                        </row>
                        <row>
                            <cell>Posodobljen</cell>
                            <cell style="text-align:right;">7.0</cell>
                            <cell>dražba</cell>
                            <cell style="text-align:right;">39.9</cell>
                        </row>
                        <row>
                            <cell>Patsy</cell>
                            <cell style="text-align:right;">6.1</cell>
                            <cell>APOD</cell>
                            <cell style="text-align:right;">37.2</cell>
                        </row>
                        <row>
                            <cell>KOEL</cell>
                            <cell style="text-align:right;">5.9</cell>
                            <cell>astronomska</cell>
                            <cell style="text-align:right;">36.4</cell>
                        </row>
                        <row>
                            <cell>[hyperlink]</cell>
                            <cell style="text-align:right;">5.9</cell>
                            <cell>premičnin</cell>
                            <cell style="text-align:right;">35.4</cell>
                        </row>
                        <row>
                            <cell>info@patsy.si</cell>
                            <cell style="text-align:right;">5.5</cell>
                            <cell>UGANKA</cell>
                            <cell style="text-align:right;">33.9</cell>
                        </row>
                        <row>
                            <cell>[hyperlink]</cell>
                            <cell style="text-align:right;">5.5</cell>
                            <cell>[hyperlink]</cell>
                            <cell style="text-align:right;">30.7</cell>
                        </row>
                        <row>
                            <cell>foodwalk</cell>
                            <cell style="text-align:right;">5.5</cell>
                            <cell>Izhodišče</cell>
                            <cell style="text-align:right;">30.3</cell>
                        </row>
                        <row>
                            <cell>Lylo</cell>
                            <cell style="text-align:right;">5.3</cell>
                            <cell>FOTOGRAFIJE</cell>
                            <cell style="text-align:right;">30.0</cell>
                        </row>
                        <row>
                            <cell>ORTO</cell>
                            <cell style="text-align:right;">5.1</cell>
                            <cell>GLASBA</cell>
                            <cell style="text-align:right;">29.6</cell>
                        </row>
                        <row>
                            <cell>UriKuri</cell>
                            <cell style="text-align:right;">4.6</cell>
                            <cell>Dopolni</cell>
                            <cell style="text-align:right;">29.5</cell>
                        </row>
                        <row>
                            <cell>yummy</cell>
                            <cell style="text-align:right;">4.6</cell>
                            <cell>UE</cell>
                            <cell style="text-align:right;">29.1</cell>
                        </row>
                        <row>
                            <cell>Ordered</cell>
                            <cell style="text-align:right;">4.4</cell>
                            <cell>javna</cell>
                            <cell style="text-align:right;">27.5</cell>
                        </row>
                        <row>
                            <cell>Shellac</cell>
                            <cell style="text-align:right;">4.4</cell>
                            <cell>sedežna</cell>
                            <cell style="text-align:right;">27.2</cell>
                        </row>
                        <row>
                            <cell>Cosmo</cell>
                            <cell style="text-align:right;">4.2</cell>
                            <cell>GCC</cell>
                            <cell style="text-align:right;">26.5</cell>
                        </row>
                        <row>
                            <cell>LPG</cell>
                            <cell style="text-align:right;">3.8</cell>
                            <cell>PRIPOROČAMO</cell>
                            <cell style="text-align:right;">26.4</cell>
                        </row>
                        <row>
                            <cell>Starševski</cell>
                            <cell style="text-align:right;">3.7</cell>
                            <cell>Espargaro</cell>
                            <cell style="text-align:right;">26.4</cell>
                        </row>
                        <row>
                            <cell>e-trgovine</cell>
                            <cell style="text-align:right;">3.5</cell>
                            <cell>[hyperlink]</cell>
                            <cell style="text-align:right;">26.3</cell>
                        </row>
                        <row>
                            <cell>[hyperlink]</cell>
                            <cell style="text-align:right;">3.5</cell>
                            <cell>zemljišča</cell>
                            <cell style="text-align:right;">26.0</cell>
                        </row>
                        <row>
                            <cell>Elle</cell>
                            <cell style="text-align:right;">3.3</cell>
                            <cell>[hyperlink]</cell>
                            <cell style="text-align:right;">25.3</cell>
                        </row>
                        <row>
                            <cell>info@tjasaseme.si</cell>
                            <cell style="text-align:right;">3.3</cell>
                            <cell>Pomurskem</cell>
                            <cell style="text-align:right;">24.8</cell>
                        </row>
                        <row>
                            <cell>boxa</cell>
                            <cell style="text-align:right;">3.2</cell>
                            <cell>ENERGIJE</cell>
                            <cell style="text-align:right;">24.5</cell>
                        </row>
                        <row>
                            <cell>derivatov</cell>
                            <cell style="text-align:right;">3.2</cell>
                            <cell>Žurnal24</cell>
                            <cell style="text-align:right;">24.4</cell>
                        </row>
                        <row>
                            <cell>IBU</cell>
                            <cell style="text-align:right;">3.1</cell>
                            <cell>LITERATURA</cell>
                            <cell style="text-align:right;">24.3</cell>
                        </row>
                        <row>
                            <cell>Onaplus</cell>
                            <cell style="text-align:right;">3.1</cell>
                            <cell>gozda</cell>
                            <cell style="text-align:right;">24.2</cell>
                        </row>
                        <row>
                            <cell>Aquafresh</cell>
                            <cell style="text-align:right;">3.0</cell>
                            <cell>[hyperlink]</cell>
                            <cell style="text-align:right;">23.5</cell>
                        </row>
                        <row>
                            <cell>naftnih</cell>
                            <cell style="text-align:right;">3.0</cell>
                            <cell>PRS</cell>
                            <cell style="text-align:right;">23.1</cell>
                        </row>
                        <row>
                            <cell>Watercolour</cell>
                            <cell style="text-align:right;">3.0</cell>
                            <cell>Ekipa24</cell>
                            <cell style="text-align:right;">22.8</cell>
                        </row>
                        <row>
                            <cell>[hyperlink]</cell>
                            <cell style="text-align:right;">3.0</cell>
                            <cell>[hyperlink]</cell>
                            <cell style="text-align:right;">22.3</cell>
                        </row>
                        <row>
                            <cell>foodwalks</cell>
                            <cell style="text-align:right;">7.7</cell>
                            <cell>Moia</cell>
                            <cell style="text-align:right;">41.7</cell>
                        </row>
                    </table>
                    <p>
                        <hi rend="bold">Gender.</hi> While a comparison of the
                        key word forms from female or male corporate accounts in Table 15 does not
                        offer any insights into possible linguistic differences between them, it
                        does give us information about differences in topics and style in regard to
                        language choices made when addressing female or male target audience. Female
                        accounts include names of magazines, URLs and proper names related to
                        fashion, shopping, food and parenting, while in male account these elements
                        are related to real estate, sport and music. </p>
                </div>
            </div>
            <div>
                <head>Conclusions</head>
                <p>Social media have revolutionized corporate communications by allowing companies
                    to communicate directly and instantly with their stakeholders, marking a shift
                    from the traditional one-way output of corporate communications, to an expanded
                    dialogue between company and consumer (<ref target="#Matthews.2010">Matthews 2010</ref>). This paper presents the
                    results of the first comprehensive, large-scale and corpus-driven analysis of
                    the characteristics of corporate communication on Twitter in Slovenia that could
                    serve as a starting-point of further, data-driven and linguistically enhanced
                    investigations of the importance of social media for fostering corporate
                    communication. In the study, we combined the analysis of the available metadata,
                    Tweet content and corpus annotations to study three key aspects of the
                    communication of Slovene corporate Twitter users: (1) the participation, posting
                    dynamics and posting volume, (2) the utilization of new media elements, and (3)
                    the language choices observed through several levels of linguistic
                    discription.</p>
                <p>Based on the Janes-Tweet corpus, Twitter appears to be mainly used for private
                    communication in Slovenia. The majority of corporate accounts belong to the
                    low-activity category but the volume of content generated by the corporate users
                    is stable. Corporate tweets are more homogenous length-wise and are
                    predominantly longer than those of private users.</p>
                <p>The analysis of the usage of the new media elements suggests that corporate
                    tweets come short of the true dialogic approach as most Slovene companies and
                    institutions use Twitter as yet another channel for unidirectional communication
                    of regular (shortened) PR messages, while the prevalent communication function
                    remains informative and positively presentational. This can be seen from a much
                    less frequent usage of emoticons and all other interactive elements typical of
                    private accounts, which display a distinct conversational communication function
                    that can be seen in their frequent usage of non-standard particles,
                    interjections, punctuation and language, and a large number of favourites.</p>
                <p>A very strong feature of corporate communication is the almost exclusive usage
                    of Slovene which is undoubtedly strategic with a clear focus on the Slovene
                    market. While standard language and formal elements do prevail in corporate
                    tweets of Slovene companies and institutions, the infrequent occurrences of
                    informal and non-standard elements seem to be used deliberately and tailored to
                    the specific target audience, which points towards a growing awareness of
                    adapting the style to the content that is communicated (level of formality,
                    linguistic standardness, discursiveness), target audience (general public –
                    neutral style vs. specific public – variations between neutral and colloquial
                    style) and the organization profile (public institution – neutral style,
                    standard language, companies – visible, colloquial, non-standard features).</p>
                <p>Both sentiment- and part-of-speech-based keyword analyses show an interesting
                    landscape of corporate tweets. The usage of evaluative adjectives is prominent
                    throughout this subcorpus, among which superlatives stands out in particular.
                    The negative keywords originate from the coverage of accidents and crimes by the
                    media, and the positive fully correspond with the definition of promotional
                    elements. These results indicate an important difference between the negative
                    reporting-style tweets by the news outlets, and the positive promotional style
                    of companies, public institutions and non-governmental institutions, suggesting
                    the need for a more fine-grained categorization of corporate accounts, which
                    will be refined in our future work. We also plan to focus on analyzing the
                    reception of corporate tweets which contain non-standard language and
                    interactive elements which are more typical of private communication on social
                    media.</p>
                <p>An important original contribution of this study is its demonstration of the
                    methodological potential of corpus approaches in communication studies, media
                    studies and related disciplines in social sciences which are based on language
                    data, which is not yet utilized in the Slovene context. Apart from theoretical
                    relevance, the results of this analysis therefore also have practical
                    implications for PR practitioners and organizations in that they reinforce the
                    importance of properly trained PR practitioners who use social media in a
                    dialogic, two-way symmetrical model, understand their role as boundary spanners
                    and the need to seek opportunities to engage in and stimulate dialogue with
                    stakeholders. The results of our study also clearly illustrate to the PR
                    practitioners that social media should not be treated as just another means
                    through which to disseminate the same advertisements and publicity pieces that
                    stakeholders are already receiving through other traditional media channels.
                    According to <ref target="#Matthews.2010">Matthews (2010)</ref>, social media offers an opportunity for direct and
                    instant corporate communication as well as an opportunity to get back to the
                    ideal basics of public relations – building and maintaining relationships – and
                    to change some of the negative stereotypes typically associated with the
                    industry.</p>
            </div>
            <div>
                <head>Acknowledgments</head>
                <p>The work described in this paper was funded by the Slovenian Research Agency
                    within the national basic research project “Resources, methods, and tools for
                    the understanding, identification, and classification of various forms of
                    socially unacceptable discourse in the information society” (J7-8280, 2017-2019)
                    and the Slovenian-Flemish bilateral basic research project “Linguistic
                    landscape of hate speech on social media” (N06-0099, 2019 – 2023).</p>
            </div>
        </body>
        <back>
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            </div>
            <div type="summary">
                <docAuthor>Darja Fišer, Monika Kalin Golob</docAuthor>
                <head style="text-transform: uppercase;">Corporate communication on Twitter
                        in Slovenia: A corpus analysis</head>
                <head rend="subheader">SUMMARY</head>
                <p>In the past decade, social media have transformed
                        corporate communications by enabling direct and instant communication with
                        the stakeholders. In communication studies, three main strands of research
                        into corporate communication practices on social media can be identified:
                        posting behaviour, content analysis and perception studies. Investigators
                        are mostly interested in corporate communication styles, reputation
                        management and corporate social responsibility. A better understanding of
                        the language practices used by public companies and institutions for
                        presentation, persuasion and reputation management on social media is still
                        lacking.
                </p>
                <p>This paper addresses this gap with the first
                        comprehensive, large-scale and corpus-driven analysis of the characteristics
                        of corporate communication on Twitter in Slovenia. In the study, we combined
                        the analysis of the available metadata, Tweet content and corpus annotations
                        in the Janes-Tweet corpus to study three key aspects of the communication of
                        Slovene corporate Twitter users: (1) their participation, posting dynamics
                        and posting volume, (2) the use of social-media specific communication
                        elements, and (3) the language choices observed through several levels of
                        linguistic discription.
                </p>
                <p>Our analysis shows that, in comparison to private
                        accounts, corporate tweets predominantly use formal communication and
                        standard language characteristics with seldom usage of informal and
                        non-standard choices. In the event of those, however, they are chosen
                        deliberately to address a specific target audience and meet the desired
                        communicative goals. The analysis of the utilisation of the new media
                        elements by corporate users clearly show that their tweets come short of the
                        true dialogic approach and that most Slovene companies and institutions use
                        Twitter as yet another channel for unidirectional communication of regular
                        (shortened) PR messages in which the prevalent communication function
                        remains informative and positively presentational. A keyword analysis
                        reveals an important difference between the negative reporting-style tweets
                        by the news outlets, and the positive promotional style of companies, public
                        institutions and non-governmental institutions, suggesting the need for a
                        more fine-grained categorization of corporate accounts, which will be
                        refined in our future work.</p>
                <p>Another major contribution of the paper is its
                        demonstration of the methodological potential of corpus approaches in
                        communication studies, media studies and related disciplines in social
                        sciences that are based on language data, which is not yet utilized in the
                        Slovene context. Apart from theoretical relevance, the results of this
                        analysis therefore also have practical implications for the PR community
                        which highlight the importance of properly trained PR practitioners who use
                        social media in a dialogic, symmetrical model, understand their role as
                        boundary spanners and the need to seek opportunities to engage in and
                        stimulate dialogue with their stakeholders.
                </p>
            </div>
            <div type="summary" xml:lang="sl">
                <docAuthor>Darja Fišer, Monika Kalin Golob</docAuthor>
                <head>SLOVENSKO KORPORATIVNO SPOROČANJE NA DRUŽBENEM OMREŽJU TWITTER: KORPUSNA ANALIZA</head>
                <head rend="subheader">POVZETEK</head>
                <p>V zadnjem desetletju so z omogočanjem neposrednega in
                        takojšnjega stika z deležniki družbena omrežja močno vplivala tudi na
                        korporativno kominiciranje. V komunikologiji korporativne komunikacijske
                        prakse na družbenih omrežjih raziskujejo z opazovanjem vedenja korporativnih
                        uporabnikov, analizo vsebine in percepcijskimi študijami. Komunikologe
                        zanimajo predvsem slogi poslovnega sporočanja, upravljanje ugleda in
                        družbena odgovornost podjetij, medtem ko še vedno primanjkujejo jezikoslovno
                        usmerjene raziskave, ki bi omogočile boljše razumevanje jezikovnih praks, ki
                        jih podjetja in institucije uporabljajo za predstavljanje svojih izdelkov,
                        vplivanje na potrošnike in odzivanje v kritičnih situacijah.</p>
                <p>To vrzel naslavlja pričujoči prispevek, v katerem
                        predstavimo prvo celovito, na obsežnem korpusu zasnovano analizo
                        korporativnega komuniciranja med slovenskimi uporabniki družbenega omrežja
                        Twitter. Izvedli smo jo s kombinacijo besedilnih podatkov, metapodatkov in
                        korpusnih oznak, ki so na voljo v korpusu Janes-Tviti, pri analizi pa smo se
                        osredotočili na tri vidike korporativnega komuniciranja v slovenskih
                        uporabnikov: (1) njihovo prisotnost, aktivnost, dinamiko in količino objav,
                        (2) rabo novomedijskih komunikacijskih elementov in (3) jezikovne izbire,
                        opazovane na različnih ravneh jezikovnega opisa.</p>
                <p>Izvedene analize so pokazale, da v primerjavi z
                        zasebnimi računi v korporativnih tvitih izrazito prevladujejo standardne
                        jezikovne prvine formalnega sporočanja, sicer redkejše neformalne in
                        nestandardne izbire pa so uporabljene premišljeno glede na naslovnika
                        sporočila in namen sporočanja. Analiza izkoriščanja novomedijskih elementov
                        jasno kaže, da komuniciranje slovenskih korporativnih uporabnikov na
                        družbenem omrežju Twitter ne sledi dialoškemu pristopu in da večina
                        slovenskih podjetij in institucij Twitter razume kot dodatni kanal za
                        enosmerno sporočanje klasičnih (skrajšanih) sporočil za javnost,
                        sporočanjska vloga katerih ostaja pretežno informativna in pozitivno
                        predstavitvena. Analiza ključnih besed razkrije pomembno razliko med
                        negativnim poročanjskim slogom medijskih računov in med pozitivnim
                        promocijskim slogom podjetij, javnih ustanov in nevladnih organizacij, kar
                        nakazuje na potrebo po natančnejši kategorizaciji korporativnih računov v
                        korpusu, ki jo načrtujemo za prihodnje raziskave.
                </p>
                <p>Pričujoči prispevek je dragocen tudi zato, ker
                        demonstrira potencial korpusnih pristopov v komunikologiji, medijskih
                        študijah in drugih sorodnih družboslovnih disciplinah, ki temeljijo na
                        jezikovnih podatkih, kar v slovenskem okolju še ni ustaljena praksa. Poleg
                        teoretične relevantnosti imajo rezultati predstavljene analize tudi
                        praktično vrednost za komunikološko stroko, saj izpostavljajo pomen ustrezno
                        usposobljenih strokovnjakov za odnose z javnostmi, ki obvladajo dialoški,
                        simetričen model družbenih omrežij, razumejo svojo posredniško vlogo med
                        deležniki in podjetjem, ki ga zastopajo, ter proaktivno iščejo priložnosti
                        za navezovanje pristnih stikov z deležniki in spodbujajo dialog z
                        njimi.</p>
            </div>
        </back>
    </text>
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