Production Volume and Vocabulary Size

As already presented in Table 1, the corpus contains nearly 41 million tokens or 35 million words. noSketch Engine also offers the lexicon size of the corpus, as given in Table 2, which shows that the corpus contains approximately 263,000 different word forms (so, inflected words, e.g., Slovenije) and over 104,000 different lemmas (so, base forms of words, e.g.,Slovenija), and 1,080 different morphosyntactic tags (e.g.,Verb main present second plural). However, it should be noted that both lemmas and the tags are automatically assigned, so they also contain some annotation errors: the accuracy of morphosyntactic tags is around 94%, the accuracy of lemmas is above 99%.

Table 2: Lexicon sizes of the Parlameter corpus. Unique words 263,007 Unique lemmas 104,247 Unique tags 1,080

While the corpus contains parliamentary debates from the period 2014-2018 (see Table 3), 62% of the material was recorded in 2015 and 2016. Given the parliamentary term, which lasted from 1 August 2014 to 14 April 2018, it is interesting to observe an 8% smaller production in 2017 compared to the year before since the last year of the term would be expectedly the busiest in order to wrap up the workplan and set the ground for a new election cycle.

Table 3: Distribution of text quantity by year in Parlameter. Year No. of tokens % of tokens Rel. freq. 2014 3,759,110 9% 91,714 2015 12,441,754 30% 303,550 2016 13,270,257 32% 323,763 2017 9,944,401 24% 242,620 2018 1,571,994 4% 38,353 Total 40,987,516 100% 1,000,000

Morphosyntactic Specificities of the Language in ParlaMeter

We performed a basic analysis of the morphosyntactic annotations of the corpus in form of the most significant differences in their frequencies between the Gigafida reference corpus of SloveneFor this comparison we used the deduplicated version of Gigafida 2.0. At the time of writing, this corpus was newly made and does not yet have a reference publication. It is, however, freely available for searching and analysis at https://www.clarin.si/noske/. and the Parlameter corpus, which are given in Table 4.The morphosyntactic tags are given here in their expanded form to aid understanding. The reference to these morphosyntactic descriptions is given in http://nl.ijs.si/ME/V6/msd/html/msd-sl.html.

Table 4: Most salient differences in morphosyntactic descriptions between Gigafida 2.0 and Parlameter. Gigafida Parlameter Residual web Pronoun personal first singular nominative Numeral roman cardinal Verb main present second plural Adjective possessive positive masculine singular instrumental Pronoun personal second masculine plural nominative Auxiliary infinitive Pronoun possessive first feminine singular genitive singular Adjective possessive positive masculine plural genitive Verb main present first plural -Negative Adjective possessive positive masculine singular locative Verb main present second plural -Negative Adjective possessive positive neuter singular locative Pronoun demonstrative neuter plural accusative Pronoun possessive third masculine singular accusative dual Pronoun personal first singular accusative Adjective possessive positive masculine singular nominative -Definiteness Verb main present first singular Pronoun possessive third feminine plural locative singular masculine Verb main present first singular Adjective possessive positive masculine plural nominative Pronoun demonstrative masculine singular dative Noun proper feminine plural dative Pronoun indefinite feminine singular genitive Numeral letter ordinal neuter plural genitive Pronoun indefinite masculine singular accusative Pronoun personal first dual accusative Verb auxiliary present second plural -Negative Pronoun personal first dual dative Verb auxiliary future first singular -Negative Noun proper neuter singular instrumental Pronoun personal first masculine plural nominative Adjective possessive positive feminine singular locative Verb auxiliary present second plural +Negative Pronoun personal second singular accusative bound Verb main present first plural Pronoun personal third masculine dual dative +Clitic Pronoun indefinite feminine singular accusative Adjective possessive positive masculine plural locative Pronoun demonstrative feminine plural accusative

The results show that the parliamentary speeches, as expected, contain more present tense verb forms, especially in the first and second person singular or plural (e.g., imamo - we have, pozdravljam - I greet, zaupate- you trust), as well as personal and demonstrative pronouns, the former most prominently as the first person singular personal pronoun (jaz - I).

On the other hand, the parliamentary proceedings do not contain URLs or Roman numerals. More interestingly, they also contain significantly fewer possessive adjectives (e.g. torkovim - Tuesday’s) and pronouns (njun - theirs[dual]), proper names, numerals, personal pronouns in the dual number (naju - us two), or in second person singular accusative (nate - to you) than general Slovene.

Language and Gender in Parlameter

As Table 5 shows, gender is recorded for all but one speaker in the corpus.This missing information is due to errors in input metadata records, which will be improved in the next version of the corpus. In total, 1,965 speakers are represented, 62% of which are male and 38% female. Interestingly, the contribution from the speakers is not proportionate to the distribution according to their gender, with the male speakers contributing 71% of the tokens in the corpus and the female speakers 29%. On the speech level the difference is even more pronounced as the male speakers delivered 73% of the speeches while female speakers only 27%, indicating that, on average, the speeches given by female speakers were somewhat longer than those by male speakers.

Table 5: Distribution of speakers and text production by gender in Parlameter. Gender No. of speakers % of speakers No. of tokens % of tokens Female 747 38% 29,147,871 71% Male 1217 62% 11,838,913 29% Unknown 1 0% 732 0% Total 1965 100% 40,987,516 100%

Table 6, which lists top-ranking 10 female and male speakers and their production in terms of tokens, shows that the most prolific male speakers produced nearly twice as much material as their female counterparts. Overall, all top 10 speakers except one (Miha Kordiš, male, the Levica party) have a leading role in one or more parliamentary or governmental bodies, including 2 ministers, both of which are female, 2 opposition deputy group chairs, who are both male, and the Chair of the National Assembly who is also male. Based on their roles in the parliament or the government, top-ranking speakers represent issues on culture, corruption, judiciary, finances, agriculture, foreign policy, education and infrastructure. In terms of political orientation, the largest opposition party SDS is best represented with 5 top-ranking male and 3 female speakers, including chair and vice-chair of their deputy group. Among the top-ranking female speakers, the entire political spectrum is represented while male speakers from the SD and DeSUS parties do not make the list, and the SMC party is only represented by the Chair of the National Assembly whose role is most likely predominantly procedural, not to promote the party agenda.

Table 6: Top-ranking 10 female and male speakers and their text production in Parlameter. Female Party affiliation // Role Tok. % Male Party affiliation // Role Tok. % Anja B. Žibert SDS // Chair of the Culture Committee 698,883 6% Jožef Horvat NSI // Chair of the Foreign Policy Committee; Chair of the Deputy Group NSI 1,141,778 4% Jelka Godec SDS // Chair of the Inquiry Commission on the Misuse Practices in Healthcare 530,029 4% Jani Möderndorfer ZAAB // Chair of the Inquiry Commission on bank money laundering; Vice-chair of the Election Committee 1,062,546 4% Iva Dimic NSI // Vice-chair of the Judiciary Committee 509,101 4% Franc Trček Levica // Vice-chair of the Infrastructure Committee; Vice-chair of the Inquiry Commission on bank money laundering 1,060,399 4% Alenka Bratušek ZAAB // Vice-chair of the Public Finances Committee; Vice-chair of the Deupty Group ZAAB 483,171 4% Milan Brglez SMC // Chair of the National Assembly; Chair of the Constitution Committee 948,334 3% Violeta Tomić Levica // Vice-chair of the Agriculture Committee 446,460 4% Vinko Gorenak SDS // Vice-chair of the Deputy Group SDS 788,678 3% Eva Irgl SDS // Chair of the petition committee 439,042 4% Franc Breznik SDS // Vice-chair of the Election Committee 763,437 3% Urška Ban SMC // Chair of the Finances and Monetary Policy Committee 382,425 3% Jože Tanko SDS // Chair of the Deputy Group SDS 752,130 3% Mateja V. Erman Minister of Finance 381,604 3% Andrej Šircelj SDS // Chair of the Public Finances Committee 721,135 2% Bojana Muršič SD // Vice-chair of the National Assembly, Vice-chair of the Education Committee 366,547 3% Tomaž Lisec SDS // Chair of the Agriculture Committee 707,666 2% Julijana B. Mlakar DeSUS // Minister of Culture; Vice-chair of the Foreign Policy Committee 308,355 3% Miha Kordiš Levica 676,717 2%

In order to compare the topics discussed by female and male speakers in the Slovene parliament, we analysed their 100 top-ranking key lemmas, where we used the corpus of all female speakers as the target corpus against the reference corpus of all male speakers in the Parlameter corpus, and vice versa, so the two lists display the distinguishing features of each of the groups. By observing their contexts via concordances, we manually classified them into one of the 13 topics represented by the ministries in the Slovenian government:

agriculture, forestry and food culture defence economy and technology education, science and sport environment and spatial planning finance health foreign affairs infrastructure interior justice labour, family and social affairs public administration

In addition, we introduced 4 additional categories for words that could not be classified into any of the topics above:

interaction/procedural for keywords which referred to other people attending the session (e.g., references to names of other speakers, predsednik - chairman) or expressed procedural matters during the session (e.g., prisotni - present, dobrodošli - welcome) style for keywords which were either distinctly colloquial or distinctly formal and were frequently used only by a single or very few speakers in order to achieve a special effect (e.g., penez, a very informal expression for money, šiht, a very informal expression for job) ideology for keywords which were used to ideologically label an individual speaker or a group of speakers (e.g., levičarski - leftist, kapitalizem - capitalism) multiple for keywords which were used in several topics (e.g., zgodnji - early, fantastičen - fantastic).

As can be seen from Table 7, the most frequent topics among the female speakers are health (35) and labour, family and social affairs (33), which are followed by public administration (13) and education, science and sport (8). Most of the 100 top-ranking keywords uttered by male speakers, on the other hand, could not be classified into a single topic because they were used either to achieve a stylistic effect (24), were general words that were used in multiple topics, such as descriptive adjectives or legal terms (22), or ideological expressions (6), all of which indicate a more discursive, debating style of the male speakers, but could also stem from the fact that the leading roles in that term were predominantly held by male members of parliament.This problem could be avoided by removing outliers regarding production in the dataset before performing the analyses. But our goal here was to present the complete corpus and demonstrate the basic corpus analysis techniques. Despite being much more infrequent than in the female part of the corpus overall, the most frequently represented specific topics by male speakers are infrastructure (9), interior (6), agriculture, forestry and food (5), and defence (5), suggesting a significant difference in the roles and interests of male and female speakers in the Slovene parliament.

Table 7: Topics of 100 top-ranking keywords of female and male speakers in Parlameter. Topics – female Freq. Topics - male Freq. health 35 style 24 labour, family & social affairs 33 multiple 22 public administration 13 infrastructure 9 education, science & sport 8 interior 6 interaction/procedural 3 ideology 6 multiple 3 interaction/procedural 5 environment & spatial planning 1 agriculture, forestry & food 5 agriculture, forestry & food 1 defense 5 culture 1 foreign affairs 4 finance 1 finance 4 economy & technology 1 justice 3 Total 100 Total 100

Illustrative examples of the 10 top-ranking female- and male-specific keywords with a manually assigned topic are listed in Tables 8 and 9.

Table 8: Most frequent keywords, topics and word type among female speakers in Parlameter. N stands for nouns, Adj for adjectives, and NP for proper nouns (names). Lemma – English translation Topic PoS Freq. Freq_ref Score rejništvo – fostercare labour, family & social affairs N 264 59 7.7 mark – mark health PN 155 29 7.1 enostarševski – single-parent labour, family & social affairs Adj 167 38 6.6 roditeljski – parent labour, family & social affairs Adj 169 39 6.5 medical – medical health PN 128 26 6.2 plazma – plasma health N 82 9 6.1 pacientov – patient’s health Adj 282 97 5.7 zaznamba – notice public administration N 155 43 5.7 žilen – stent health Adj 518 213 5.4 duševen – mental health Adj 393 156 5.4 nasilnež – violent person labour, family & social affairs N 98 21 5.4 Table 9: Most frequent keywords, topics and word type among male speakers in Parlameter. lemma – English translation category PoS Freq_ref Score penez – inf. money finance N 0 13.2 navsezadnje – nevertheless multiple Adv 90 8.4 kubik – cubic agriculture, forestry & food N 10 7.8 islam – Islam interior N 6 6.4 levičarski – leftist ideology Adj 2 6.2 navzoč – present interaction/procedural Adj 211 6.0 avtošola – driving school infrastructure N 1 5.8 socialist – socialist ideology N 25 5.5 svojevrsten – peculiar multiple Adj 16 5.4 e-klopa – e-bench interaction/procedural N 1 5.3 prečenje – crossing style N 3 5.2

That the nature and style of male speeches is quite different from the female ones can also be seen from the analysis of the morphosyntactic types of 100 highest-ranking keywords for male and female speakers. While nouns are the most frequent category and are used equally frequently by both male and female speakers (44%), many more adjectives were found among the female top-ranking keywords (33% vs. 16%), while the male keywords had more adverbs (11% vs. 4%) and verbs (9% vs. 2%), which again could be related to the roles of the speakers in the parliament. However, given the results of our preliminary work on this dataset (Ljubešić et al. 2018), during which we removed the speakers that produced most of the linguistic material from the analysis, we see similar trends both in the gender-dependent keyword and morphosyntactic analysis, and are therefore rather in favour of accepting the observed differences as impact of gender and not role.

Language and Party Affiliation in Parlameter

Affiliation is recorded for only 113 speakers out of the 1982, however, these are responsible for 79% of the tokens in the corpus. Affiliation is considered as either deputy group membership or a role in the government, where it must be noted that in this version of the corpus the metadata reflect the situation at the beginning of the term and does not keep track of party membership transfers or resignations of ministers or members of parliament. Also, when elected members of parliament were later appointed as ministers, the metadata record only their party affiliation and records as ministers only those who were appointed without being first elected to the parliament. To facilitate more fine-grained and accurate use of the corpus in political science or contemporary history, we plan to refine the metadata for the next release of the corpus, adding also the MP’s membership in the working bodies of the National Assembly, etc. Also, the metadata in the current version of the corpus do not flag the independent members of parliament who do not belong to any of the parliamentary parties and operate in the Independents deputy group, which is why they are not included in our analysis.

As Table 10 shows, the most prolific deputy group is the largest opposition party Slovenian Democratic Party (SDS), whose 20 members contributed nearly 10 million tokens or 30% of the corpus. SDS is followed by the main governing party, Party of Modern Centre (SMC), whose 42 members contributed 7 million tokens or 22% of the corpus. It is interesting to note that in terms of the volume contributed to the corpus on one side and the number of speakers on the other, that this party was the least productive among the main parties, with a ratio of the percentage of tokens to the percentage of speakers (i.e., the relative token to speaker ratio) of 0.54, which means that this party generated a little bit more than a half of the material that would have been expected given their number of speakers and the overall activity of all the speakers. The Left (Levica) and New Slovenia (NSi) rank third and fourth, despite the fact that they had only 6 members each in the parliament, making them the most productive parties with a relative token to speaker ratio of 1.83 and 1.66. The Democratic Party of Pensioners of Slovenia had as many as 12 elected MPs but contributed 1 million tokens less than the two previous parties, which makes them the second least productive party with a relative token to speaker ratio of 0.67.

Table 10: Distribution of speakers and text production by party affiliation in ParlaMeter with speakers with unknown affiliation removed.The number of speakers per party is calculated from the ParlaMeter dump and deviates slightly from the official member number due to different handling of speakers with multiple roles. Affiliation No. of speakers % of speakers No. of tokens % of tokens Slovenian Democratic Party Deputy Group (SDS) 20 20% 9.516.651 30% Party of Modern Centre Deputy Group (SMC) 42 41% 7.162.719 22% The Left Deputy Group (Levica) 6 6% 3.438.194 11% New Slovenia – Christian Democrats Deputy Group (NSI) 6 6% 3.370.131 10% Social Democrats Deputy Group (SD) 9 9% 2.533.019 8% Democratic Party of Pensioners of Slovenia Deputy Group (DeSUS) 12 12% 2.435.884 8% Party of Alenka Bratušek Deputy Group (SAB) 4 4% 1.876.294 6% Italian and Hugarian National Minorities Deputy Group (IMNS) 2 2% 117.709 0% Government 1 1% 1.765.374 5% Total 102 100% 32.215.975 100%

Next, we performed a manual analysis of the 100 top-ranking keywords of each political party against the rest of the corpus (see Table 12). These analyses display the distinct properties of one party that are not shared by other parties. Using the concordances, we classified the keywords into the same categories as in Section 4.1, the results of which are summarized in Table 11.

Table 11: Topics of 100 top-ranking keywords of party members in Parlameter. Topics SMC DeSUS SD SDS NSi Levica SAB agriculture, forestry & food 0 0 34 0 27 0 0 culture 0 3 0 0 0 1 0 defense 0 0 21 5 0 0 1 economy & technology 0 0 5 1 11 13 1 education, science & sport 0 0 0 0 0 0 4 environment & spatial planning 0 0 3 0 6 1 0 finance 0 2 2 0 6 1 1 foreign affairs 0 5 0 2 4 3 0 health 0 3 0 8 1 0 5 ideology 0 0 0 15 3 9 0 infrastructure 1 0 2 0 7 1 1 interaction/procedural 99 61 14 17 10 4 14 interior 0 0 0 3 0 3 5 justice 0 1 1 8 0 0 0 labour, family & social affairs 0 13 3 1 4 13 3 multiple 0 2 6 13 8 17 29 public administration 0 2 0 5 2 1 7 style 0 8 9 22 11 33 29 Total 100 100 100 100 100 100 100

Unsurprisingly, due to the role of the main governing party SMC, practically all their top-ranking keywords are interactional elements with the other speakers or have a procedural nature (e.g., navzoč – present, glasovanje – voting, amandma – amendment). That DeSUS is a single-issue party can be seen from their keywords, which, apart from a surprisingly high proportion of interactive keywords, belong almost exclusively to the semantic field of retirement and pension (e.g., regres – holiday pay, valorizirati – to revalue, gmoten – material). Interestingly, even the topics of foreign affairs and culture are nearly completely absent from their keyword list, despite the fact that these ministers came from their party, suggesting that these topics are more or less evenly shared with other parties. SD, the third coalition party, clearly display their priority areas of agriculture, forestry and food (e.g., teran – Teran wine, fermentiran – fermented, kmetovati – to farm) and defence (e.g., vojakinja – female soldier, neeksplodiran – unexploded, strelivo – ammunition), which can be traced back to their ministers.

The largest opposition party SDS stands out from the rest by the amount of ideological keywords identified among the top-ranking keywords (e.g. tranzicijski – transitional, totalitarizem – totalitarism, lustracija – lustration). NSi and Levica, the opposition parties with the same number of MPs but from the opposite ends of the political spectrum, both address the widest variety of issues (their keywords were classified into 13 out of 18 topics). The topics with nearly equal number of completely opposite keywords are economy and technology (e.g. soupravljanje – co-management for Levica vs. espejevec – private entrepreneur for NSi). While NSi mostly talks about the local issues related to their constituencies (e.g. samooskrba – self-sufficiency, posekan – cut down, obdelovati - farm), Levica stands out by signature stylistic devices which range from very informal (e.g. šlamastika – pickle, gazda – informal for master, nabijati – to bang on) to highly elevated registers (e.g. nemara – perhaps, onkraj – beyond, ducat – dozen) and displays the largest proportion of ideological vocabulary next to SDS (e.g. tovarišica – camerade, revizionizem – revisionism, imperializem – imperialism). SAB seems to stand out by a predominantly (local) administrative/procedural/governance vocabulary (e.g. proporcionalen – proportional, odpoklic – recall, dvokrožen – double-ballot) as well as a discursive, informal style of distinctly negative sentiment, which is characteristic of one of their members Vinko Möderndorfer (e.g. rešpektiram - honour, kozlarija - nonsense, zmazek - disaster).

Table 12: 100 top-ranking keywords per political party, taking into account lowercased lemmas, computed against the rest of the Parlameter corpus and sorted according to their keyness score. SMC navzoč, e-klopa, udis, roberto, prekinjen, podprogram, prehajati, lipicer, kustec, katerim, grebenšek, h, battelli, epi, stanujoč, obveščati, krajnc, zaključevati, predajati, pričenjati, sodin, porotnica, simona, franc, glasovati, obrazložitev, moderen, kolegij, tanko, postopkovno, potisek, končevati, nuklearen, brezpredmeten, ep, jernej, dneven, počkaj, glasovnica, mandatno-volilen, vojko, jožef, trček, bojan, neusklajen, tilen, prelog, ustavnorevizijski, odločanje, arko, nadomeščati, he, branislav, matej, jože, glasovanje, prvopodpisan, e-klop, glas, dopolnjen, porotnik, terminski, vložen, simono, franca, pogačnik, erman, ugotavljati, klanjšček, smc, stebernak, nepovezan, jana, žibert, bien, matjaž, šircelj, fajt, postopkoven, lilijana, skrajšan, monetaren, prekinjati, poslovniški, matičen, bah, mag., marinka, šergan, lenča, vraničar, , izvolitev, karlovšek, razpravljavec, predstavnica, razširitev, anita, amandma, nadomeščanje, zame DeSUS meglič, črnak, pripadajoč, desus, pogačar, dasiravno, vukov, valenca, požun, inferioren, upajoč, mӧderndorfer, pregrešiti, divjak, valorizacija, korva, rezime, kkr, kuzmanič, marijan, upokojen, vuk, mehčati, pojbič, košnik, bližnjevzhoden, zaposlovalen, punkcija, žmavc, milojka, zaporedno, celarc, konzularen, xv., marija, kolar, bačič, erika, grošelj, rubelj, minski, lukić, rudarski, zadržanost, mirjam, godec, valorizirati, sng, tašner, kušar, brinovšek, invalid, zamrznitev, tedaj, dvoživkarstvo, nina, pirnat, dekleva, merše, federacija, nada, klanjšček, protiukrep, jelka, ogrizek, gmoten, kisikov, ivo, majcen, izvoliti, iva, dimic., modifikacija, ljubič, žan, upokojenec, prikrajšanje, prečitati, šimenko, jasna, izplačevanje, zipro, korpič, antonija, premožen, sapa, voljč, suzana, dimic, vesni, lukič, zdravko, irena, teja, sluga, regres, ruše, janja, razparava, trivialen SD izčistiti, genetsko, izčiščen, vezava, surov, demokrat, vojakinja, gorsko-hribovski, travinje, potočan, vadišče, razprodati, hip, služenje, hišniški, faktorski, pripadnica, stiskanje, zmogljivost, omd-, kočevski, anhovo, vrtojba, peterica, mineralen, maji, krušen, kmetica, ciolos, vklop, deti, socialdemokratski, formacijski, teran, selnica, kloniran, urszr, obramben, salonit, radeče, mlekarna, neperspektiven, marjana, popolnjevanje, omd, odzivanje, vrtnina, vselej, zorganizirati, vikariat, eutm, pokolp, govedo, rogaška, klirinški, razprodaja, surovina, ksenija, vinko, izčiščevati, konzumen, refundirati, pripadnik, neeksplodiran, social, uokviriti, žito, kfor, prebroditi, konvergenca, grajski, brecelj, hogan, administriranje, trader, kočevsko, h4, primož, korenjak, bržkone, kmetovati, obrtništvo, vojska, strelivo, poveljevanje, snežnik, plasiran, gorsko, refundacija, hribovski, proizvodnja, subvencijski, dacian, missing, kmetija, opazovati, voditeljstvo, kramar, fermentiran, viher SDS islam, fišer, mark, svinjarija, levičarski, odnosno, medical, kb, demokratski, odnosen, lenart, zemljarič, kučan, zalar, bordojski, kb1909, morišče, zločin, iznenada, velikanski, tomos, kangler, patria, multikulti, masleša, prvorazreden, škrlec, udba, stožice, tranzicijski, šef, praprotnik, moralno-etičen, ilegalno, zločinski, bomben, peticija, porsche, srebrenica, cener, umor, totalitaren, pokrasti, totalno, genocid, drugorazreden, tamle, erdogan, judikat, vega, ribičič, privilegiranec, komunističen, razorožitev, varnostnoobveščevalen, žilen, opornica, indičen, škandal, ornik, lustracija, poljanski, posavje, počenjati, furlan, pobiti, sevnica, ubog, janković, krkovič, npu, deček, opran, bojda, blamaža, lopov, toplak, kerševan, slikati, bmw, veselo, amen, totalen, komunizem, totalitarizem, obsoditi, preiskati, bedarija, udbovski, pomorjen, turnšek, vladavina, zlagati, šoping, vpiti, ukc, avion, klemenčič, koruptiven, neumnost NSI komunalno, socialno-tržen, marn, božičnica, zidanica, egalitaren, krščanski, espejevec, fantastičen, ekstrapolacija, planšarija, medparlamentaren, kamnik, demografija, kapica, bundestag, podonavski, bajuk, samoprispevek, vinogradnik, razlastiti, vipavski, prijateljstvo, kanalizacija, aksiom, pomurje, bogataš, ferenc, parcelacija, optimirati, oljčnik, komenda, polnost, vrtalec, ozp, pomurski, ikt, simulirati, dimniški, parlamentarec, podčrtovati, artikulirati, obžalovati, omizje, cerknica, polčas, ginijev, zbirno-reciklažen, brutalno, prekladanje, širokogruden, absorpcijski, šinko, dolenjsko, lestev, vodovod, rodnost, traktor, notranjska, opn, posekan, vinograd, zaraščati, odvajanje, loža, kristjan, davno, regresen, lovrenčič, firefox, parcela, akrapovič, obdelovati, obratovalnica, zpn, terezija, mihael, odlašati, peskovci, vamp, notranjski, ovs, copatek, veselica, upniški, penzija, hala, digitalen, goljuf, identifikacijski, mohar, postoriti, goveji, prirasti, splačati, samooskrba, prazniti, odstaven, todorić, pozor Levica penez, tuliti, vračljivost, ubesedovati, onkraj, bajta, neoliberalen, prečiti, nemara, ducat, socialist, delavski, imperialističen, zvrniti, desnica, navsezadnje, blazen, sociolog, šiht, soupravljanje, zategovanje, mandarin, kapitalizem, strokovec, šlamastika, blazno, kapitalističen, tovarišica, ubesedovanje, revizionizem, prekarnost, vzdržan, gazda, profit, sodržavljanka, izkoriščevalski, represija, protisocialen, nabijati, prekaren, metafora, soodločanje, periferen, agregaten, cinkarna, rezilen, mezda, amandmiranje, demokratizacija, ips, efektivno, natov, levica, belokranjec, bučka, zaposlovalec, izhajajoč, reven, požegnati, profiten, marof, ics, minimalec, podrejati, imperializem, kapitalist, silno, prekarizacija, odpustek, sodržavljan, noveliranje, versus, zvo, bolgarski, zastraševanje, informatičen, metaforično, režati, razreden, ciničen, striči, ropotati, korporacija, rasizem, redistributiven, pregrevanje, trade, rez, omv, prekeren, deregulacija, štacuna, grosist, znoreti, penzion, oligopolen, jahati, fevdalizacija, sočasno, prečenje SAB svojevrsten, večnost, mvk, pooblaščati, that's, diskvalifikacija, prekleto, bla, resnica, fakt, naglas, odpoklic, zavezništvo, minis, četrten, trapast, istrabenz, zasebništvo, zamah, dvokrožen, ramšakov, diskvalificirati, športnica, drk, štos, cetera, ups, nedostojno, redarski, strojan, nijz, proporcionalen, ma, evtanazija, zanič, bloudkov, etc, mv, vsakič, naturalizacija, zamera, nor, listnica, smešiti, dispečiranje, diskusija, strašansko, nefer, diskutirati, regres, sprevržen, r., zavrtanik, večen, hiv, nekorektno, ubežati, imperativen, presedan, prastrah, dinozaver, halo, ekstremističen, rimskokatoliški, mvk-, namenoma, zmazek, gedrih, somalijski, zamahniti, nonstop, kostanjevec, policaj, domišljati, prohibicija, znakoven, paradoks, barantati, et, hecen, močvirnik, avans, nametati, preprosto, prepričevati, podžupan, traparija, kričati, ekstra, non-stop, telovadba, stefanovič, el-zoheiry, ničkolikokrat, kozlarija, prvenstvo, boh, domišljija, rešpektiram

The Zeitgeist of ParlaMeter

Finally, we observe the zeitgeist of the Parlameter corpus by comparing it with its older and smaller cousin, the SlovParl corpus, which contains material from the period of Slovenia’s independence (1990-1992). First, we created keyword lists with each of the two corpora acting as a focus and a reference corpus (see Table 14). We then manually classified 100 top-ranking keywords into the same categories as in Section 4.1, with the following additional categories:

abbreviations (etc., Mr.), which were in use in the SlovParl but are no longer the convention in the ParlaMeter transcriptions of the parliamentary sessions IT vocabulary (internet, web), which at the time of SlovParl was not yet widespread.

If we disregard the differences in the mentions of the active politicians in the two periods, which are the most frequent category, most of the top-ranking keywords in both corpora belong to procedural and legal issues, which are clearly different in a newly established state and a state integrated in the EU (see Table 13). Apart from that, many more topics are identified in the Parlameter corpus, such as economy and technology, foreign affairs and health, which again is not surprising as a well-established state will need to take care of a full spectrum of issues.

Table 13: Topics of the 100 top-ranking keywords in Parlameter and SlovParl. Topic ParlaMeter SlovParl abbreviation 0 3 defence 0 1 economy & technology 6 2 education 1 0 environment & spatial planning 2 0 finance 12 7 foreign affairs 4 0 health 4 0 multiple 0 1 informal vocabulary 2 0 infrastructure 1 0 interior 2 0 it vocabulary 2 0 justice 1 0 labour, family & social affairs 3 0 legal/procedural 14 21 politician/party 46 65 Total 100 100 Table 14: 100 top-ranking keywords in Parlameter contrasted against SlovParl and vice versa. ParlaMeter evro, eu, desus, smc, cerar, sdh, dutb, möderndorfer, trček, bratušek, sds, gorenak, spleten, mandatno-volilen, deležnik, koalicijski, kordiš, anja, matej, direktiva, postopkovno, kpk, okoljski, kohezijski, javnofinančen, tonin, bdp, veber, naročanje, korupcija, bah, jani, levica, nlb, unija, tanko, migrantski, povprečnina, vatovec, čakalen, pojbič, migrant, varuhinja, prikl, žnidar, šircelj, varuh, zujf, teš, violeta, tomić, mahnič, ddv, digitalen, han, istospolen, lisec, telekom, vrtovec, dars, žibert, novela, globa, zorčič, vajeništvo, godec, trošarina, čuš, okrožen, internet, prvopodpisan, schengenski, matić, trajnosten, gašperšič, jurša, podneben, dz, lipica, lah, podizvajalec, žan, uredba, blagajna, okej, verbič, ferluga, dobovšek, mramor, računski, vraničar, zakonik, ljudmila, nevladen, postopkoven, preiskovalen, direktorat, hanžek, muršič, irgl SlovParl delegat, oz., glavič, družbenopolitičen, gros, dinar, republiški, usklajevalen, din, skupščinski, starman, zakonjšek, alinea, vzdržati, potrč, vzdržan, kolešnik, izvršen, lukač, sklepčnost, pintar, npr., navzočnost, buser, arzenšek, feltrin, atelšek, liberalno-demokratski, smole, razpravljalec, školč, zvezen, schwarzbartl, delegatski, tomšič, zagožen, železarna, jakič, gošnik, skupščina, polajnar, tomažič, muren, štefančič, lastninjenje, deviza, zlobec, šter, demos, dretnik, kreditno-monetaren, sdp, čimprej, nabornik, devizen, marka, delegatka, sekretariat, bekeš, deželak, klavora, peterle, črnej, halb, kreft, šonc, lokar, gradišar, šeligo, juri, perko, sfrj, voljč, požarnik, semolič, volilec, kramarič, bučar, plebiscit, dvornik, tomše, grašič, tolar, starc, pregelj, podobnik, pozsonec, balažic, g., moge, medzborovski, jaša, razdevšek, rojec, šetinc, urbančič, lavtižar-bebler, vivod, anka, šešok

To illustrate differences in the zeitgeist of both corpora, we extracted the strongest collocations of the following 3 expressions, which are frequent in both corpora, taking into account the collocation candidates that appear at least 5 times immediately next (left or right) to the headword, and analysed the first 50 collocation candidates:

adjective južen – southern, noun kriza – crisis, and verb sprožiti – trigger. Table 15: Comparison of collocations of južen, kriza and sprožiti in SlovParl and ParlaMeter. Topics or morphosyntactic categories are indicated in square brackets, and new collocations in Parlameter are highlighted in bold. SlovParl ParlaMeter južen

178 (14.03 per million)

[GEOGRAPHY]: koreja, primorska, amerika [CONCRETE]: meja, železnica [METAPHORICAL]: trg, del, stran, republika

910 (22.20 per million)

[GEOGRAPHY]: afrika, koreja, sredozemlje, amerika, tirolska, sudan, tirolec, koroška, italija, evropa, nemčija, slovenija [CONCRETE]: meja, obvoznica, tok, sadje, odsek, železnica, ulica [METAPHORICAL]: sosedstvo, soseda, sosed, soseščina, del, trg, projekt, stran, država, republika sprožiti

548 (43.19 per million)

[CONCRETE]: spor, postopek, proces, interpelacijo, arbitražo [METAPHORICAL]: reakcijo, polemiko, akcijo, mehanizem, pobudo, vprašanje, diskusijo, zahtevo, spremembo, razpravo, zadevo

1,569 (38.28 per million)

[CONCRETE]: postopek, spor, preiskavo, alarm, process, ovadbo, tožbo, stečaj, prijavo, revizijo [METAPHORICAL]: plaz, mehanizem, polemiko, reakcijo, kepo, pobudo, akcijo, iniciativo, aktivnost, debato, kampanjo kriza

1,114 (87.79 per million)

[GEOGRAPHY]: jugoslovanska, zalivska kriza [POLITICS]: vladna, gospodarska, parlamentarna, ekonomska, ustavna, politična kriza [METAPHORICAL]: duševna, socialna, razvojna, družbena kriza [MODIFIERS]: huda, moralna, globoka, katastrofalna, velika, težka kriza [NOUNS]: reševanje, razrešitev, rešitev, razplet, razreševanje krize [VERBS]: prebroditi, poglabljati, razrešiti, povzročiti, rešiti, začeti krizo

8,062 (196.69 per million)

[GEOGRAPHY]: ukrajinska, grška, svetovna, globalna kriza [POLITICS]: migrantska, begunska, gospodarska, finančna, migracijska, humanitarna, ekonomska, dolžniška, bančna, politična, begunsko-migrantska, mlečna, javnofinančna, varnostna, kapitalistična kriza [METAPHORICAL]: socialna kriza [MODIFIERS]: huda, kompleksna, globoka, velika kriza [NOUNS]: začetek, breme, izbruh, nastop, posledica, nastanek, reševanje, obdobje krize [VERBS]: kriza nastopi, nastane, pokaže, udari // povzročiti, reševati, poglabljati krizo

As can be seen from Table 15, the biggest difference in relative frequency between the two corpora is observed for the noun crisis, which is more than twice as frequent in Parlameter compared to SlovParl, despite the fact that the early 1990s were marked by a long and bloody war in the Balkans as well as severe economic hardship related to change of the economic and political system. Parlameter contains the largest number of new collocation candidates that indicate issues that were not present in the period of SlovParl, such as migrant/refugee/humanitarian/security crisis. On the other hand, the secession period was marked by constitutional/parliamentary crisis, which are not observed in the late 2010s. Interestingly, SlovParl contains more metaphorical collocations which are not prominent in the Parlameter corpus, such as mental/social/welfare/moral crisis. Collocations containing geographical terms indicate the key political, military and social hotspots from that period: Yugoslav/Gulf crisis in early 1990s, and Ukraine/Greek crisis in late 2010s. An analysis of key verbal collocates with the noun crisis reveals another interesting observation, which is that in SlovParl, all the verbs are about solving the crisis (to solve/resolve/untangle the crisis), whereas in Parlameter, politicians mostly use verbs that discuss the beginnings or deepening of the crisis (crisis sets in/appears/starts/hits, to trigger/deepen the crisis).

The verb trigger is the only one of the three examples that has a higher relative frequency in SlovParl but despite the greater relative frequency, Parlameter contains more collocation candidates, both in the direct and the metaphorical sense, such as trigger an investigation/indictment/lawsuit, or trigger an audit/bankruptcy.

It is interesting to note that the adjective southern is more frequently used and has more collocations in general in ParlaMeter despite the fact that in the secession period, links to the rest of former Yugoslavia were probably stronger and there were probably more open issues, signalling that certain topics were probably not discussed on purpose until the issues were resolved and the relations were established again. Especially interesting are all the neighbour-related collocations, which only appear in the Parlameter corpus, 30 years after Slovenia left Yugoslavia: southern neighbour / neighbours / neighbourhood / market / fruit, despite the fact that geographically speaking, the former Yugoslav republics, spread south-east, not south of Slovenia. The one major unsettled issue is the border with Croatia that has even been subject of international arbitration during the parliamentary term included in the Parlameter corpus, which is reflected in the top-ranking strong collocation južna meja/southern border.