Abstract
We examine a network of over 40,000 tweets posted before the 2019 European election in Slovenia. The discussion observed is highly polarized: analysis of communication patterns reveals a partisan structure with limited connectivity between centre-left and right-leaning clusters. Users tend to communicate with like-minded peers and share content originating from their own communities. Bridges – accounts enabling the diffusion of content between ideologically different communities – are almost non-existent. Right-wing politicians are among the most prominent users in the network and can dominate the discourse within their communities. This shows that politicians effectively use Twitter as a strategic communications tool to engage with their supporters, spread their partisan messages and make use of the polarized social media environment. The data mirrors findings from other democracies, providing further evidence that polarization of political discourse is a prominent feature of the contemporary communication environment, present across various national, geographical and political contexts.
About the author
independent researcher
References
Aral, S. (2020). The hype machine: How social media disrupts our elections, our economy, and our health – and how we must adapt. Currency.Suche in Google Scholar
Arguedas, A. R., Robertson, C. T., Fletcher, R., & Nielsen, R. K. (2022). Echo chambers, filter bubbles, and polarisation: A literature review. Digital News Project – Reuters Institute. https://reutersinstitute.politics.ox.ac.uk/sites/default/files/2022-01/Echo_Chambers_Filter_Bubbles_and_Polarisation_A_Literature_Review.pdfSuche in Google Scholar
Barberá, P. (2014, September 3–6). How social media reduces mass political polarization. Evidence from Germany, Spain, and the US [Paper presentation]. American Political Science Association Annual Meeting 2015, San Francisco, CA, United States. http://pablobarbera.com/static/barbera_polarization_APSA.pdfSuche in Google Scholar
Barberá, P., Jost, J. T., Nagler, J., Tucker, J. A., & Bonneau, R. (2015). Tweeting from left to right: is online political communication more than an echo chamber? Psychological Science, 26(10), 1531–1542. https://doi.org/10.1177/095679761559462010.1177/0956797615594620Suche in Google Scholar
Bastos, M., Mercea, D., & Baronchelli, A. (2018). The geographic embedding of online echo chambers: Evidence from the Brexit campaign. PLoS ONE, 13(11), 1–16. https://doi.org/10.1371/journal.pone.020684110.1371/journal.pone.0206841Suche in Google Scholar
Benkler, Y., Faris, R., Roberts, H., & Zuckerman, E. (2017). Breitbart-led right-wing media ecosystem altered broader media agenda. Columbia Journalism Review. https://www.cjr.org/analysis/breitbart-media-trump-harvard-study.phpSuche in Google Scholar
Borgesius, Z., Trilling, D., Möller, J., Bodó, B., de Vreese, C. H., & Helberger, N. (2016). Should we worry about filter bubbles? Internet Policy Review, 5(1). https://doi.org/10.14763/2016.1.40110.14763/2016.1.401Suche in Google Scholar
Bracciale, R., Martella, A., & Visentin, C. (2018). From super-participants to super-echoed: participation in the 2018 Italian electoral twittersphere. Partecipazione e Conflitto, 11(2), 361–393. https://doi.org/10.1285/i20356609v11i2p361Suche in Google Scholar
Bright, J., Marchal, N., Ganesh, B., & Rudinac, S. (2020). Echo chambers exist! (But they’re full of opposing views). ArXiv. http://arxiv.org/abs/2001.11461Suche in Google Scholar
Bruns, A. (2017). Echo chamber? What echo chamber? Reviewing the evidence. 6th Biennial Future of Journalism Conference, UK, 0–11.Suche in Google Scholar
Bruns, A. (2019). Are filter bubbles real?. Polity Press.10.14763/2019.4.1426Suche in Google Scholar
Bruns, A. (2023). From “the” public sphere to a network of publics: Towards an empirically founded model of contemporary public communication spaces. Communication Theory, 33(2–3), 70–81. https://doi.org/10.1093/CT/QTAD00710.1093/ct/qtad007Suche in Google Scholar
Bruns, A., & Highfield, T. (2016). Is Habermas on Twitter? Social media and the public sphere. In A. Bruns, G. Enli, E. Skogerbo, A. O. Larsson, & C. Christensen (Eds.), The Routledge companion to social media and politics (pp. 98–130). Routledge.10.4324/9781315716299Suche in Google Scholar
Carpentier, N. (2017). The discursive-material knot. Peter Lang Publishing. https://doi.org/10.3726/978-1-4331-3754-910.3726/978-1-4331-3754-9Suche in Google Scholar
Casero-Ripollés, A. (2021). Influencers in the political conversation on Twitter: Identifying digital authority with big data. Sustainability, 13(5), 2851. https://doi.org/10.3390/SU1305285110.3390/su13052851Suche in Google Scholar
Casero-Ripollés, A., Alonso-Muñoz, L., & Marcos-García, S. (2021). The influence of political actors in the digital public debate on Twitter about the negotiations for the formation of the government in Spain. American Behavioral Scientist, 66(3), 307–322. https://doi.org/10.1177/0002764221100315910.1177/00027642211003159Suche in Google Scholar
Ceia, V. (2020). Digital ecosystems of ideology: Linked media as rhetoric in Spanish political tweets. Social Media and Society, 6(2). https://doi.org/10.1177/205630512092663010.1177/2056305120926630Suche in Google Scholar
Cota, W., Ferreira, S. C., Pastor-Satorras, R., & Starnini, M. (2019). Quantifying echo chamber effects in information spreading over political communication networks. EPJ Data Science, 8(1), 35. https://doi.org/10.1140/epjds/s13688-019-0213-910.1140/epjds/s13688-019-0213-9Suche in Google Scholar
Dehghan, E. (2020). Networked discursive alliances: Antagonism, agonism, and the dynamics of discursive struggles in the Australian Twittersphere [Doctoral dissertation, Queensland University of Technology]. QUT ePrints. https://doi.org/10.5204/thesis.eprints.17460410.5204/thesis.eprints.174604Suche in Google Scholar
Diani, M. (2003). “Leaders” Or Brokers? Positions and Influence in Social Movement Networks. In M. Diani & D. McAdam (Eds.), Social Movements and Networks: Relational Approaches to Collective Action (pp. 105–122). Oxford University Press. https://doi.org/10.1093/0199251789.003.000510.1093/0199251789.003.0005Suche in Google Scholar
Dubois, E., & Blank, G. (2018). The echo chamber is overstated: The moderating effect of political interest and diverse media. Information Communication and Society, 21(5), 729–745. https://doi.org/10.1080/1369118X.2018.142865610.1080/1369118X.2018.1428656Suche in Google Scholar
Dubois, E., & Gaffney, D. (2014). The multiple facets of influence: Identifying political influentials and opinion leaders on Twitter. American Behavioral Scientist, 58(10), 1260–1277. https://doi.org/10.1177/000276421452708810.1177/0002764214527088Suche in Google Scholar
Dugué, N., & Perez, A. (2022). Direction matters in complex networks: A theoretical and applied study for greedy modularity optimization. Physica A: Statistical Mechanics and Its Applications, 603, 127798. https://doi.org/10.1016/J.PHYSA.2022.12779810.1016/j.physa.2022.127798Suche in Google Scholar
Erdös, P. and Rényi, A. (1960). On the Evolution of Random Graphs. Publication of the Mathematical Institute of the Hungarian Academy of Sciences, 5(1), 17–61.Suche in Google Scholar
Esteve Del Valle, M., & Borge Bravo, R. (2018). Leaders or brokers? Potential influencers in online parliamentary networks. Policy & Internet, 10(1), 61–86. https://doi.org/10.1002/POI3.15010.1002/poi3.150Suche in Google Scholar
Esteve Del Valle, M., Broersma, M., & Ponsioen, A. (2022). Political interaction beyond party lines: communication ties and party polarization in parliamentary Twitter networks. Social Science Computer Review, 40(3), 736–755. https://doi.org/10.1177/089443932098756910.1177/0894439320987569Suche in Google Scholar
Eurostat. (2022). Individuals – internet activities (ISOC_CI_AC_I). https://ec.europa.eu/eurostat/databrowser/view/ISOC_CI_AC_I__custom_8570330/default/table?lang=en&page=time:2020Suche in Google Scholar
Firdaus, S. N., Ding, C., & Sadeghian, A. (2018). Retweet: A popular information diffusion mechanism – A survey paper. Online Social Networks and Media, 6, 26–40. https://doi.org/10.1016/J.OSNEM.2018.04.00110.1016/j.osnem.2018.04.001Suche in Google Scholar
Freelon, D. (2018). Partition-specific network analysis of digital trace data. In B. F. Welles, S. González-Bailón (Eds.), The Oxford Handbook of Networked Communication (pp. 1–27). Oxford University Press. https://doi.org/10.1093/oxfordhb/9780190460518.013.310.1093/oxfordhb/9780190460518.013.3Suche in Google Scholar
Freeman, L. C. (1977). A set of measures of centrality based on betweenness. Sociometry, 40(1), 35–41. https://doi.org/10.2307/303354310.2307/3033543Suche in Google Scholar
Garimella, K., De Francisci Morales, G., Gionis, A., & Mathioudakis, M. (2018). Political discourse on social media: Echo chambers, gatekeepers, and the price of bipartisanship. Proceedings of the 2018 World Wide Web Conference on World Wide Web, France, 913–922. https://doi.org/10.1145/3178876.318613910.1145/3178876.3186139Suche in Google Scholar
Ghajar-Khosravi, S., & Chignell, M. (2017). Pragmatics of network centrality. In L. Sloan, & A. Quan-Haase (Eds.), The Sage handbook of social media research methods (pp. 309–327). Sage Publications Ltd.10.4135/9781473983847.n19Suche in Google Scholar
Graham, T., & Wright, S. (2014). Discursive equality and everyday talk online: the impact of “superparticipants”. Journal of Computer-Mediated Communication, 19(3), 625–642. https://doi.org/10.1111/jcc4.1201610.1111/jcc4.12016Suche in Google Scholar
Hallin, D. C., & Mancini, P. (2004). Comparing Media Systems: Three Models of Media and Politics. Cambridge University Press. https://doi.org/10.1017/CBO978051179086710.1017/CBO9780511790867Suche in Google Scholar
Herrero, L., Humprecht, E., Engesser, S., Brüggemann, M., & Büchel, F. (2017). Rethinking Hallin and Mancini beyond the west: An analysis of media systems in Central and Eastern Europe. International Journal of Communication, 11, 4797–4823. https://ijoc.org/index.php/ijoc/article/view/6035/2196Suche in Google Scholar
Hong, S., & Kim, S. H. (2016). Political polarization on twitter: Implications for the use of social media in digital governments. Government Information Quarterly, 33(4), 777–782. https://doi.org/10.1016/J.GIQ.2016.04.00710.1016/j.giq.2016.04.007Suche in Google Scholar
Indridason, I. H. (2008). Multiparty democracy: Elections and legislative politics. Perspectives on Politics, 6(1), 195–196. https://doi.org/10.1017/S153759270808041910.1017/S1537592708080419Suche in Google Scholar
Jacomy, M., Venturini, T., Heymann, S., & Bastian, M. (2014). ForceAtlas2, a continuous graph layout algorithm for handy network visualization designed for the Gephi software. PLoS ONE, 9(6), e98679. https://doi.org/10.1371/journal.pone.009867910.1371/journal.pone.0098679Suche in Google Scholar
Jungherr, A., Rivero, G., & Gayo-Avello, D. (2020). Retooling politics. Cambridge University Press. https://doi.org/10.1017/978110829782010.1017/9781108297820Suche in Google Scholar
Just, N., & Latzer, M. (2016). Governance by algorithms: Reality construction by algorithmic selection on the Internet. Media, Culture & Society, 39(2), 238–258. https://doi.org/10.1177/016344371664315710.1177/0163443716643157Suche in Google Scholar
Kekkonen, A., & Ylä-Anttila, T. (2021). Affective blocs: Understanding affective polarization in multiparty systems. Electoral Studies, 72, 102367. https://doi.org/10.1016/J.ELECTSTUD.2021.10236710.1016/j.electstud.2021.102367Suche in Google Scholar
Kinkead, D., & Douglas, D. M. (2020). The network and the demos: Big data and the epistemic justifications of democracy. In K. Macnish & J. Galliott (Eds.), Big data and democracy (pp. 119–134). Edinburgh University Press. https://www.cambridge.org/core/books/big-data-and-democracy/network-and-the-demos-big-data-and-the-epistemic-justifications-of-democracy/AA98E294F857F1EE3DC6B803E1957AAB10.3366/edinburgh/9781474463522.003.0009Suche in Google Scholar
Krackhardt, D., & Stern, R. N. (1988). Informal networks and organizational crises: An experimental simulation. Social Psychology Quarterly, 51(2), 123. https://doi.org/10.2307/278683510.2307/2786835Suche in Google Scholar
Kubin, E., & von Sikorski, C. (2021). The role of (social) media in political polarization: A systematic review. Annals of the International Communication Association, 45(3), 188–206. https://doi.org/10.1080/23808985.2021.197607010.1080/23808985.2021.1976070Suche in Google Scholar
Lasser, J., Aroyehun, S. T., Simchon, A., Carrella, F., Garcia, D., & Lewandowsky, S. (2022). Social media sharing by political elites: An asymmetric American exceptionalism. ArXiv. http://arxiv.org/abs/2207.06313Suche in Google Scholar
Lynch, M., Freelon, D., & Aday, S. (2017). Online clustering, fear and uncertainty in Egypt’s transition. Democratization, 24(6), 1159–1177. https://doi.org/10.1080/13510347.2017.128917910.1080/13510347.2017.1289179Suche in Google Scholar
Marwick, A., & Lewis, R. (2017). Media manipulation and disinformation online. Data & Society. https://datasociety.net/output/media-manipulation-and-disinfo-online/Suche in Google Scholar
Micó, J. L., & Casero-Ripollés, A. (2014). Political activism online: organization and media relations in the case of 15M in Spain. Information, Communication & Society, 17(7), 858–871. https://doi.org/10.1080/1369118X.2013.83063410.1080/1369118X.2013.830634Suche in Google Scholar
Miconi, A., & Papathanassopoulos, S. (2023). On Western and Eastern media systems: Continuities and discontinuities. In: S. Papathanassopoulos & A. Miconi (Eds.), The Media Systems in Europe. (pp. 15–34). Springer. https://doi.org/10.1007/978-3-031-32216-7_210.1007/978-3-031-32216-7_2Suche in Google Scholar
Newman, M. E. J., & Girvan, M. (2003). Finding and evaluating community structure in networks. Physical Review E – Statistical, Nonlinear, and Soft Matter Physics, 69(2). https://doi.org/10.1103/PhysRevE.69.02611310.1103/PhysRevE.69.026113Suche in Google Scholar
Nguyen, C. T. (2020). Echo chambers and epistemic bubbles. Episteme, 17(2), 141–161. https://doi.org/10.1017/epi.2018.3210.1017/epi.2018.32Suche in Google Scholar
Orhan, Y. E. (2022). The relationship between affective polarization and democratic backsliding: comparative evidence. Democratization, 29(4), 714–735. https://doi.org/10.1080/13510347.2021.200891210.1080/13510347.2021.2008912Suche in Google Scholar
Örnebring, H. (2012). Clientelism, elites, and the media in Central and Eastern Europe. The International Journal of Press/Politics, 17(4), 497–515. https://doi.org/10.1177/194016121245432910.1177/1940161212454329Suche in Google Scholar
Papacharissi, Z. (2016). The virtual sphere: The internet as a public sphere. New Media & Society, 4(1), 9–27. https://doi.org/10.1177/1461444022222624410.1177/14614440222226244Suche in Google Scholar
Pariser, E. (2011). The filter bubble: What the internet is hiding from you. Penguin UK.10.3139/9783446431164Suche in Google Scholar
Reiljan, A. (2020). ‘Fear and loathing across party lines’ (also) in Europe: Affective polarisation in European party systems. European Journal of Political Research, 59(2), 376–396. https://doi.org/10.1111/1475-6765.1235110.1111/1475-6765.12351Suche in Google Scholar
Soares, F. B., Recuero, R., & Zago, G. (2018). Influencers in polarized political networks on Twitter. Proceedings of the 9th International Conference on Social Media and Society, 168–177. https://doi.org/10.1145/3217804.321790910.1145/3217804.3217909Suche in Google Scholar
Stromer-Galley, J. (2017). Political discussion and deliberation online. In K. Kenski, & K. H. Jamieson (Eds.), The Oxford Handbook of Political Communication (pp. 837–851). Oxford University Press. https://doi.org/10.1093/oxfordhb/9780199793471.013.015_update_00110.1093/oxfordhb/9780199793471.013.015_update_001Suche in Google Scholar
Stroud, N. J. (2010). Polarization and partisan selective exposure. Journal of Communication, 60(3), 556–576. https://doi.org/10.1111/j.1460-2466.2010.01497.x10.1111/j.1460-2466.2010.01497.xSuche in Google Scholar
Sunstein, C. (2017). #Republic: Divided Democracy in the Age of Social Media. Princeton University Press.10.1515/9781400884711Suche in Google Scholar
Törnberg, P., Andersson, C., Lindgren, K., & Banisch, S. (2021). Modeling the emergence of affective polarization in the social media society. PLOS ONE, 16(10), e0258259. https://doi.org/10.1371/JOURNAL.PONE.025825910.1371/journal.pone.0258259Suche in Google Scholar
Tucker, J., Guess, A., Barbera, P., Vaccari, C., Siegel, A., Sanovich, S., Stukal, D., & Nyhan, B. (2018). Social media, political polarization, and political disinformation: a review of the scientific literature. William & Flora Hewlett Foundation. https://doi.org/10.2139/ssrn.314413910.2139/ssrn.3144139Suche in Google Scholar
Valicon. (2020). Uporaba družbenih omrežij in storitev klepeta v Sloveniji 2018 – 2019 [Use of Social Networks and Chat Services in Slovenia 2018–2019]. https://www.valicon.net/sl/2020/01/uporaba-druzbenih-omrezij-in-storitev-klepeta-v-sloveniji-2018-2019Suche in Google Scholar
Van Bavel, J. J., Rathje, S., Harris, E., Robertson, C., & Sternisko, A. (2021). How social media shapes polarization. Trends in Cognitive Sciences, 25(11), 913–916. https://doi.org/10.1016/j.tics.2021.07.01310.1016/j.tics.2021.07.013Suche in Google Scholar
van Dijk, J., & Hacker, K. L. (2018). Internet and democracy in the network society. Routledge. https://doi.org/10.4324/978135111071610.4324/9781351110716Suche in Google Scholar
van Vliet, L., Törnberg, P., & Uitermark, J. (2020). The Twitter parliamentarian database: Analyzing Twitter politics across 26 countries. PLoS ONE, 15(9 September), 1–24. https://doi.org/10.1371/journal.pone.023707310.1371/journal.pone.0237073Suche in Google Scholar
Williams, H. T. P., McMurray, J. R., Kurz, T., & Hugo Lambert, F. (2015). Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change, 32, 126–138. https://doi.org/10.1016/J.GLOENVCHA.2015.03.00610.1016/j.gloenvcha.2015.03.006Suche in Google Scholar
Wilson, A. E., Parker, V., & Feinberg, M. (2020). Polarization in the contemporary political and media landscape. Current Opinion in Behavioral Sciences, 34, 223–228. https://doi.org/10.1016/J.COBEHA.2020.07.00510.1016/j.cobeha.2020.07.005Suche in Google Scholar
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