Corporate Communication on Twitter in Slovenia: A Corpus Analysis
UDC: 003.295:659.4+004.738.5(497.4) )"201"
IZVLEČEK
SLOVENSKO KORPORATIVNO SPOROČANJE NA DRUŽBENEM OMREŽJU TWITTER: KORPUSNA ANALIZA
1V 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.
2Ključne besede: korporativno komuniciranje, družbena omrežja, Twitter, korpusna analiza
Abstract
1The 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.
2Keywords: corporate communication, social media, Twitter, corpus analysis
1. Introduction
1In the past decade, social media have evolved into a powerful tool, attracting millions of users every day (Boyd and Ellison 2007). Jansen et al. (2010) 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, Wu et al. (2011) 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 (Griffiths and McLean 2014) through which companies address a wide range of goals, such as increased traffic and brand awareness, improved search engine rankings or increased sales (Thoring 2011). In addition, social media can also be used for customer service and market research (Weber 2009).
2With 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 (Park et al. 2012) and that tweets containing words which indicate either positive or negative sentiment tend to receive more retweets than neutral posts (Stieglitz and Dang-Xuan 2012). Stelzner (2010) and Heaps (2009) 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 (Clark and Melancon 2013; Li et al. 2013; Miller and Tucker 2013). It is therefore surprising that while the new platform of engagement with customers has shifted the company–customer discourse, Mangold and Faulds (2009) show that communication is still predominantly scripted, promotion-centric and lacks real interaction with the customers.
3In 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 (Erjavec et al. 2018) 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.
4The 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.
2. Related Work
1In 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.
2Quantitative differences in communication dynamics, style and content of Slovene private and corporate Twitter users have been identified by Ljubešić and Fišer (2016) 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.
3By 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 (Waters and Jamal 2011; Xifra and Grau 2010) 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 (Kalin Golob et al. 2018). However, as shown by Kwon and Sung (2011), 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. Risius and Beck (2015) 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.
4Gomez and Chalmeta (2013) 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.
5Li et al. (2013) 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.
6In 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).
3. Corpus Analysis of Corporate Communication on Twitter
1The analysis has been performed on the Janes-Tweet corpus (Erjavec et al. 2018) 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.
2Our 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-analysis1 suite (Killgarriff et al. 2014).
3The 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?
3.1. Account Analysis
| Users | No. of users (%) | No. of tokens (%) | No. of tweets (%) |
|---|---|---|---|
| Corporate | 2612 (25.57%) | 30,003,182 (18.70%) | 2,112,910 (18.64%) |
| Private | 7627 (74.44%) | 130,401,083 (81.30%) | 9,223,736 (81.36%) |
| Total | 10,248 (10.00%) | 160,404,265 (100.00%) | 11,336,646 (100.00%) |
1Share of users. 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.
| Gender | Corporate | Private | ||
|---|---|---|---|---|
| no. of tweets | % | no. of tweets | % | |
| Unknown | 1,730,258 | 81.89% | 134,048 | 1.45% |
| Male | 271,729 | 12.86% | 6,136,470 | 66.53% |
| Female | 110,923 | 5.25% | 2,953,218 | 32.02% |
| Total | 2,112,910 | 100.00% | 9,223,736 | 100.00% |
2Users’ gender. 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.
3.2. Posting Analysis
1Post quantity. 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.
| Corporate | Private | |||
|---|---|---|---|---|
| No. of all accounts | 2612 | % | 7627 | % |
| > 10,000 tweets | 29 | 1.11% | 129 | 1.69% |
| Between 10,000 and 1,000 tweets | 422 | 16.16% | 1867 | 24.48% |
| Between 1,000 and 100 tweets | 1640 | 62.79% | 4055 | 53.17% |
| < 100 tweets | 521 | 19.95% | 1576 | 20.66% |
2Post length. 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.
3.3. Analysis of Interactive Elements
1Likes. 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.
| No. of likes | ||||
|---|---|---|---|---|
| Corporate users | Private users | |||
| No. of tweets | % | No. of tweets | % | |
| 0 | 1,663,755 | 78.74% | 610,9048 | 66.23% |
| 1 | 265,385 | 12.56% | 1,890,549 | 20.50% |
| 2-10 | 175,788 | 8.32% | 1,160,057 | 12.58% |
| >10 | 7,982 | 0.38% | 64,082 | 0.69% |
| Total | 2,112,910 | 100.00% | 9,223,736 | 100.00% |
| No. of retweets | ||||
| Corporate users | Private users | |||
| No. of tweets | % | No. of tweets | % | |
| 0 | 1,754,988 | 83.06% | 8,414,713 | 91.23% |
| 1 | 219,698 | 10.40% | 490,346 | 5.32% |
| 2-10 | 134,184 | 6.35% | 300,319 | 3.26% |
| >10 | 4,040 | 0.19% | 18,358 | 0.19% |
| Total | 2,112,910 | 100.00% | 9,223,736 | 100.00% |
| Hashtags | |||
|---|---|---|---|
| Abs. freq. | Per million | Per tweet | |
| Corporate | 922,504 | 30,746.9 | 0.44 |
| Private | 2,241,693 | 17,190.8 | 0.24 |
| Emoji | |||
| Abs. freq. | Per million | Per tweet | |
| Corporate | 1,285,696 | 42,852.0 | 0.61 |
| Private | 12,061,885 | 92,498.3 | 1.31 |
| Hyperlinks | |||
| Abs. freq. | Per million | Per tweet | |
| Corporate | 1,989,643 | 66,314.4 | 0.94 |
| Private | 2,583,651 | 19,813.1 | 0.28 |
| Mentions | |||
| Abs. freq. | Per million | Per tweet | |
| Corporate | 659,211 | 21,971.4 | 0.31 |
| Private | 9,216,857 | 57,460.2 | 1.00 |
2Retweets. 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.
3Use of hashtags. 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.
4Use of emoticons and emojis.2 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.
5As 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.
| Corporate users | Private users | ||
|---|---|---|---|
| Hashtag | Frequency | Hashtag | Frequency |
| #plts | 18,03 | #plts | 26,370 |
| #slonews | 18,247 | #slonews | 18,270 |
| #PLTS | 9,620 | #junaki | 18,167 |
| #Ljubljana | 5,724 | #slochi | 13,195 |
| #izvršba | 5,167 | #PLTS | 10,943 |
| #NKDomzale | 4,437 | #Slovenia | 10,780 |
| #olimpija | 4,176 | #Ljubljana | 10,141 |
| #rokomet | 4,143 | #radiobattleSI | 9,184 |
| #junaki | 3,941 | #ligaprvakov | 9,091 |
| #skupajdovrha | 3,864 | #sp14si | 8,351 |
| Emoji | Frequency | User | Frequency | Rel. freq3 |
|---|---|---|---|---|
| :) | 114,602 | RecycleMan | 530 | 12.711,5 |
| ;) | 55,763 | JennParisBags | 188 | 11.522,1 |
| :D | 17,715 | EtiVelikonja | 160 | 10.409,8 |
| <3 | 13,688 | ApartmaNet | 184 | 10.104,9 |
| :-) | 9,672 | TRENDtrgovina | 436 | 10.049,3 |
| ;-) | 4,926 | Pawla40 | 228 | 9.720,0 |
| :)) | 4,680 | iPlacesi | 125 | 8.860,0 |
| ❤ | 3,679 | bozicluka | 92 | 8.290,2 |
| :P | 3,558 | matejgaber22 | 99 | 7.222,6 |
| 😉 | 3,436 | Modniovitki | 424 | 7.010,9 |
6Use of hyperlinks. 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.
7Mentions of other users. 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.
| Corporate users | Private users | |||
|---|---|---|---|---|
| Mention | Frequency | Mention | Frequency | |
| @YouTube | 8,325 | @petrasovdat | 91,328 | |
| @Nova24TV | 6,903 | @YouTube | 71,859 | |
| @Val202 | 3,992 | @MarkoSket | 57,333 | |
| @rtvslo | 3,866 | @JJansaSDS | 53,482 | |
| @kzssi | 3,736 | @lucijausaj | 51,391 | |
| @unionolimpija | 3,616 | @leaathenatabako | 44,453 | |
| @JJansaSDS | 3,464 | @petrajansa | 44,102 | |
| @radioPrvi | 3,128 | @savicdomen | 43,394 | |
| @vladaRS | 2,764 | @darkob | 42,363 | |
| @nkmaribor | 2,758 | @zzTurk | 40,534 | |
3.4. Language Analysis
1Language of tweets. 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).
| Language | Corporate | Private | ||
|---|---|---|---|---|
| No. of tweets | % | No. of tweets | % | |
| Slovene | 1,973,677 | 93.41% | 8,074,681 | 87.54% |
| English | 104,955 | 4.97% | 983,141 | 10.66% |
| Bosnian/Croatian/Serbian | 16,058 | 0.76% | 57,017 | 0.62% |
| Other | 18,220 | 0.86% | 108,897 | 1.18% |
| Total | 2,112,910 | 100.00% | 9,223,736 | 100.00% |
2Sentiment of tweets. Every tweet in the corpus is annotated with a sentiment label (see Erjavec et al. 2018). 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.
| sentiment | corporate | private | ||
|---|---|---|---|---|
| no. of tweets | % | no. of tweets | % | |
| positive | 1,024,238 | 48.48% | 2,320,841 | 25.16% |
| neutral | 729,811 | 34.54% | 4,411,516 | 47.83% |
| negative | 358,861 | 16.98% | 2,491,379 | 27.01% |
| total | 2,112,910 | 100.00% | 9,223,736 | 100.00% |
3Language standardness. 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.
| Standardness | Corporate | Private | ||
|---|---|---|---|---|
| No. of tweets | % | Sentiment | No. of tweets | |
| L1 | 1,688,244 | 79.90% | 4,515,310 | 48.95% |
| L2 | 353,397 | 16.73% | 3,489,743 | 37.83% |
| L3 | 71,269 | 3.37% | 1,218,683 | 13.21% |
| 2,112,910 | 100.00% | 9,223,736 | 100.00% | |
| Part of speech | Corporate (per million) | Private (per million) | Ratio4 |
|---|---|---|---|
| Proper nouns | 66,738.4 | 33,507.8 | 1.99 |
| Numerals | 30,564.9 | 16,109.7 | 1.90 |
| Conjunctions | 54,381.1 | 33,302.1 | 1.63 |
| Prepositions | 86,947.2 | 54,549.6 | 1.59 |
| Adjectives | 76,889.9 | 48,254.8 | 1.59 |
| Common nouns | 186,446.6 | 127,056.0 | 1.47 |
| Abbreviations | 3,826.0 | 3,458.9 | 1.11 |
| Punctuation | 143,234.6 | 158,188.2 | 0.91 |
| Main verbs | 62,631.9 | 75,795.7 | 0.83 |
| Auxiliary verbs | 36,974.7 | 52,968.0 | 0.70 |
| Adverbs | 38,192.1 | 55,483.1 | 0.69 |
| Pronouns | 39,118.2 | 62,678.8 | 0.62 |
| Particles | 19,816.6 | 35,540.7 | 0.56 |
| Interjections | 1,740.9 | 6,194.5 | 0.28 |
4Orthography. Great differences are detected regarding the use of abbreviations: corporate tweets mainly contain standard abbreviations of academic or other titles (dr., mag., d. o. o.) and common abbreviations (št., oz., min.), while in private tweets we find nonstandard abbreviations (tw), often without full stop (slo, lj, min). 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 (#, @, *).
5Parts of speech. 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.
6The noun. 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%): 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. Among the 20 most frequent nouns, the following are specific to corporate tweets: video/video, foto/photo, zmaga/victory, novica/news, cena/price, sezona/season. 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%: Slovenija/Slovenia, Ljubljana, Maribor, EU, Slovenc/Slovene, Evropa/Europe, ZDA/USA, Cerar, Janša. Among the 20 most frequent nouns, the following proper nouns are corporate tweets: Olimpija, Koper, Peter, Gorica, Janez, Domžale, Luka, Tina, Marko.
7In 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 (nam/to us, nas/us, vam/to you), while in private tweets we find singular forms of pronouns (jaz/I, me/of me, ti/to you, te/you). 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.
8The verb. 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% (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), 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: želeti/wish, preveriti/check, najti/find, iskati/search, prebrati/read, gledati/watch, moči/able, hoteti/want, narediti/do.
9The adjective. 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%: nov/new, dober/good, slovenski/Slovenian, velik/big, lep/beautiful, zadnji/last, mlad/young, star/old, pravi/real, super/super. Among the 20 most frequent adjectives the following are specific to corporate tweets: vabljen/invited, današnji/today’s, evropski/European, javen/public, spleten/web/based, svetoven/world/wide, odličen/excellent, državen/national, visok/high, domač/domestic. Positive adjectives are characteristic of corporate tweets (nov/new, dober/good, velik/big, lep/beautiful) which are also more formal than the adjectives characteristic of private tweets (vabljen/invited, odličen/excellent, visok/high vs. hud/badass, mali/little, sam/alone). Adjectival as well as nominal pronouns are used in the first person plural form in corporate tweets (naše/our-Female, naši/our-Male) 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 (Korošec 1998).
10The particle. 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 (morda/maybe, predvsem/above all, sicer/though, skoraj/nearly) and nonstandard and informal particles for private tweets (tud < tudi/also; ze < že/already, itak/off course, pač/well).
11The interjection. 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%: bravo, hm, haha, uf, o, ej, ah, ha, aha, aja, oh. Among the most frequent interjections that are distinctive for one of the user groups are the following ones: živjo, zdravo, hej, hehe, gooool, opa, ups, na, ojoj. Interjections in corporate tweets are fewer in quantity as well as more formal and salutatory (zdravo, ups), while private tweets often contain interjections in foreign language (btw, lol) and swear words.
3.5. Keyword Analysis
1This 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.
| Negative | Keyness index | Positive | Keyness index | Neutral | Keyness index |
|---|---|---|---|---|---|
| oviran | 22.2 | čestitka | 3.5 | novice.si | 10.1 |
| trčenje | 19.1 | vabljen | 3.5 | zemljišče | 8.7 |
| trčiti | 18.0 | bravo | 3.4 | pivniški | 8.3 |
| priključek | 15.4 | album | 3.4 | ebel | 8.3 |
| evakuirati | 15.3 | beautiful | 3.4 | katarinin | 8.1 |
| ranjen | 15.1 | hvala | 3.4 | petv | 8.0 |
| poškodovan | 15.0 | posted | 3.4 | šloganje | 7.9 |
| razcep | 14.9 | photos | 3.4 | solaten | 7.8 |
| novicejutro.si | 14.9 | odličen | 3.3 | ugnati | 7.8 |
| osumljen | 14.6 | polepšati | 3.3 | pripravljalen | 7.7 |
| nesreča | 14.5 | odlično | 3.3 | koel | 7.6 |
| aretirati | 14.3 | prijeten | 3.3 | novinec | 7.6 |
| avtocesta | 14.1 | super | 3.3 | napovednik | 7.4 |
| neurje | 14.1 | čudovit | 3.3 | zoofa | 7.3 |
| strmoglaviti | 13.9 | čestitati | 3.3 | prerokovanje | 7.3 |
| osumljenec | 13.1 | srečno | 3.3 | poiesis | 7.2 |
| magnituda | 13.1 | 3.3 | apod | 7.1 | |
| prometen | 12.8 | welcome | 3.3 | wt | 7.1 |
| ubit | 12.8 | summer | 3.3 | sklepen | 6.9 |
2Sentiment. 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., trčenje/collision, evakuirati/evacuate, ranjen/injured, nesreča/accident). The 20 top-ranking keywords with positive sentiment correspond to the definitions of positive PR communication (e.g., čestitka/congratulations, vabljen/invited, bravo/bravo, čudovit/wonderful, polepšati/make sbd’s (day)). Adjectives and adverbs with highly positive meaning are also ranked high (e.g., lep/beautiful, odličen, odlično/fantastic, prijeten/nice, super/super). Furthermore, the 20 top-ranking keywords with neutral sentiment are part of the tweets containing media reports (e.g., novice.si/news.si, zemljišče/property, napovednik/preview, sklepen/final) and denote events (e.g., pivniški/beer, ebel/ebel, šloganje/card-reading, prerokovanje/fortune-telling) or names (katarinin, ebel, zoofa, apod). 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.
| Standard tweets | Keyness index | Non-standard tweets | Keyness index |
|---|---|---|---|
| Izkl | 6.4 | Posetite | 562.3 |
| Novice.SI | 6.4 | potrazi | 557.6 |
| dražba | 6.0 | sjajan | 553.5 |
| [hyperlink] | 5.9 | Jeste | 455.0 |
| SiOL | 5.8 | tim | 308.5 |
| Petv | 5.8 | [hyperlink] | 307.2 |
| APOD | 5.8 | [hyperlink] | 186.6 |
| Moia | 5.7 | li | 166.4 |
| spletnem | 5.7 | koketo | 145.9 |
| Zurnal24 | 5.7 | trombeto | 143.3 |
| ugodne | 5.7 | [hyperlink] | 130.0 |
| astronomska | 5.7 | belooranžnega | 129.5 |
| SMUČANJE | 5.6 | deejaytime | 111.2 |
| KOŠARKA | 5.6 | Živjo | 111.0 |
| oviran | 5.6 | Skupne | 109.6 |
| [hyperlink] | 5.6 | pritisne | 92.8 |
| ALPSKO | 5.6 | oglasiš | 66.2 |
| HOKEJ | 5.6 | [hyperlink] | 65.9 |
| zamudite | 5.6 | cheers | 60.3 |
| Preverite | 5.5 | hajskul | 56.5 |
| Nogometaši | 5.5 | [hyperlink] | 49.6 |
| TENIS | 5.5 | gnargnar | 49.6 |
| ciganskih | 5.4 | sporočimo | 47.0 |
| NOGOMET | 5.4 | najbrš | 46.8 |
| ROKOMET | 5.4 | pridte | 45.3 |
| [hyperlink] | 5.4 | javimo | 41.9 |
| Astrolife.si | 5.4 | Poslali | 41.5 |
| Izbrane | 5.4 | dm | 41.2 |
| Slovenske | 5.4 | javiš | 41.2 |
| SMUČARSKI | 5.4 | unc | 41.0 |
3Standardness. 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., dražba/auction, ugodne/good, zamudite/miss, preverite/check). 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. 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).
| Female | Keyness index | Male | Keyness index |
|---|---|---|---|
| foodwalks | 7.7 | Moia | 41.7 |
| Posodobljen | 7.0 | dražba | 39.9 |
| Patsy | 6.1 | APOD | 37.2 |
| KOEL | 5.9 | astronomska | 36.4 |
| [hyperlink] | 5.9 | premičnin | 35.4 |
| info@patsy.si | 5.5 | UGANKA | 33.9 |
| [hyperlink] | 5.5 | [hyperlink] | 30.7 |
| foodwalk | 5.5 | Izhodišče | 30.3 |
| Lylo | 5.3 | FOTOGRAFIJE | 30.0 |
| ORTO | 5.1 | GLASBA | 29.6 |
| UriKuri | 4.6 | Dopolni | 29.5 |
| yummy | 4.6 | UE | 29.1 |
| Ordered | 4.4 | javna | 27.5 |
| Shellac | 4.4 | sedežna | 27.2 |
| Cosmo | 4.2 | GCC | 26.5 |
| LPG | 3.8 | PRIPOROČAMO | 26.4 |
| Starševski | 3.7 | Espargaro | 26.4 |
| e-trgovine | 3.5 | [hyperlink] | 26.3 |
| [hyperlink] | 3.5 | zemljišča | 26.0 |
| Elle | 3.3 | [hyperlink] | 25.3 |
| info@tjasaseme.si | 3.3 | Pomurskem | 24.8 |
| boxa | 3.2 | ENERGIJE | 24.5 |
| derivatov | 3.2 | Žurnal24 | 24.4 |
| IBU | 3.1 | LITERATURA | 24.3 |
| Onaplus | 3.1 | gozda | 24.2 |
| Aquafresh | 3.0 | [hyperlink] | 23.5 |
| naftnih | 3.0 | PRS | 23.1 |
| Watercolour | 3.0 | Ekipa24 | 22.8 |
| [hyperlink] | 3.0 | [hyperlink] | 22.3 |
| foodwalks | 7.7 | Moia | 41.7 |
4Gender. 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.
4. Conclusions
1Social 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 (Matthews 2010). 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.
2Based 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.
3The 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.
4A 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).
5Both 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.
6An 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 Matthews (2010), 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.
5. Acknowledgments
1The 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).
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Darja Fišer, Monika Kalin Golob
Corporate communication on Twitter in Slovenia: A corpus analysis
SUMMARY
1In 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.
2This 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.
3Our 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.
4Another 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.
Darja Fišer, Monika Kalin Golob
SLOVENSKO KORPORATIVNO SPOROČANJE NA DRUŽBENEM OMREŽJU TWITTER: KORPUSNA ANALIZA
POVZETEK
1V 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.
2To 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.
3Izvedene 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.
4Pričujoči 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.
* 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
** Chair of Journalism, Faculty of Social Sciences, University of Ljubljana, Kardeljeva ploščad 5, SI-1000 Ljubljana, monika.kalin-golob@fdv.uni-lj.si
1. The corpus is publically available for download as well as for on-line querying through the CLARIN.SI research infrastructure.
2. Emoticons (e.g. ;)) are combinations of standard typographical characters used for expressing emotions. Emojis are pictograms (e.g. 🎂) which include emotions as well as a broad range of other topics and their usage and interpretation depend on the individual.
3. Relative frequency is the average frequency of the phenomenon in one million tokens.
4. Ratio between the frequency in corporate and in private tweets.