Hate speech as an indicator of affective political polarization during mobilization: from measurement to forecasting
https://doi.org/10.31249/poln/2025.01.07
Abstract
The article examines the phenomenon of affective political polarization, which is operationalized through the fact of detected hate speech. In this study we have made two assumptions. Firstly, it is believed that during political mobilization, affective polarization (hate speech) will be significantly stronger than during the non-protest period. Although, hate speech will be detected for both periods. Secondly, we believe protest significantly affects cleavages. During the period of protest mobilization, political cleavages become more important than social ones. To verify the assumptions, we examined data collected on the VK social network in two periods: July–September 2019 (Moscow protests) and March–May 2019 (without protests). The results of the analysis, based on the automatic mapping (ruBERT) and on the human mapping of independent encoders, confirm both assumptions. We prove both assumptions via cross correlation analysis. Moreover, present approach to data collection and mapping allows us to create predictive models (SARIMAX) to predict hate speech in a social network.
About the Author
E. V. Kruchinskaia
https://www.hse.ru/staff/ekruchinskaia
HSE University
Russian Federation
HSE University
Russian Federation
Kruchinskaia Ekaterina
Moscow
References
1. Agadullina E.R., Gulevich O.A. “We” and “they”: assistance in intergroup relations. Psychological research: electronic scientific journal. 2013, Vol. 6, N 28. DOI: https://doi.org/10.54359/ps.v6i28.703 (In Russ.)
2. Aken B. van, Risch J., Krestel R., Löser A. Challenges for Toxic Comment Classification: An In-Depth Error Analysis. In: Fišer D., Huang R., Prabhakaran V., Voigt R., Waseem Z., Wernimont J. (eds). Proceedings of the 2nd Workshop on Abusive Language Online (ALW2). Brussels, Belgium: Association for computational linguistics, 2018, Р. 33–42. DOI: https://doi.org/10.18653/v1/W18-5105
3. Aleskerov F.T., Golubenko M.A. On the assessment of the symmetry of political views and the polarization of society. Working paper WP7/2003/04 series “Mathematical methods of decision analysis in economics, business and politics”. Moscow: Higher School of Economics, 2003, 24 р. (In Russ.)
4. Akhremenko A.S. Internet shutdown as a theoretical problem of political science, or what we (don't) understand about online protest mobilization. Polis. Political research. 2024, N 2, Р. 118–134. DOI: https://doi.org/10.17976/jpps/2024.02.09 (In Russ.)
5. Bakshy E., Messing S., Adamic L.A. Exposure to ideologically diverse news and opinion on Facebook. Science. 2015, N 348, Р.1130–1132.
6. Bauer M., Christopher B., Chytilova J., Joseph H., Miguel E., Mitts T. Can war foster cooperation? Journal of economic perspectives. 2016, N 30 (3), Р. 249–274.
7. Berntzen L.E., Kelsall H., Harteveld E. Consequences of affective polarization: Avoidance, intolerance and support for violence in the United Kingdom and Norway. European journal of political research. 2024, N 63, Р. 927–949. DOI: https://doi.org/10.1111/1475-6765.12623
8. Bodrunova S., Blekanov I., Smoliarova A., Litvinenko A. Beyond left and right: real-world political polarization in Twitter discussions on inter-ethnic conflicts. Media and communication. 2019, N 7 (3), Р. 119–132. DOI: https://doi.org/10.17645/mac.v7i3.1934
9. Breuer A., Landman T., Farquhar D. Social media and protest mobilization: Evidence from the Tunisian revolution. Democratization. 2015, N 22 (4), Р. 764–792. DOI: https://doi.org/10.1080/13510347.2014.885505
10. Campbell A., Converse P., Miller W., Stokes D. The American voter. New York: John Wiley & Sons, 1960, 576 p.
11. Cantini R., Marozzo F., Talia D., Trunfio P. Analyzing political polarization on social media by deleting bot spamming. Big data and cognitive computing. 2022, N 6 (1), P. 1–16. DOI: http://doi.org/10.3390/bdcc6010003 Castaño-Pulgarín S.A., Suárez-Betancur N., Vega L.M., López H.M. Internet, social media and online hate speech. Systematic review. Aggression and violent behavior. 2021, N 58 (6), 101608. DOI: http://doi.org/10.1016/j.avb.2021.101608
12. Clark M.D., Bland D., Livingston J.A. Lessons from# McKinney: Social media and the interactive construction of police brutality. The Journal of social media in society. 2017, N 6 (1), Р. 284–313.
13. Collins R. C-Escalation and D-Escalation: A theory of the time-dynamics of conflict. American sociological review. 2012, N 77 (1), Р. 1–20. DOI: https://doi.org/10.1177/0003122411428221
14. Collins R. Violence: A micro-sociological theory. Princeton: Princeton University Press, 2008, 584 p. DOI: http://doi.org/10.1515/9781400831753
15. Coser L. Functions of social conflict. New York: Free Press, 1956, 188 p.
16. Costa M. Ideology, not affect: what Americans want from political representation. American journal of political science. 2020, Vol. 65, N 2, P. 342–358 DOI: https://doi.org/10.1111/ajps.12571
17. Del Vicario M., Vivaldo G., Bessi A., Zollo F., Scala A., Caldarelli G., Quattrociocchi W. Echo chambers: emotional contagion and group polarization on Facebook. Scientific reports. 2016, N 6, P. 1–14. DOI: https://doi.org/10.1038/srep37825
18. DiMaggio P., Evans J., Bryson B. Have American’s social attitudes become more polarized? American journal of sociology. 1996, N 102 (3), Р. 690–755.
19. Druckman J.N., Green D.P., Iyengar S. Does affective polarization contribute to democratic backsliding in America? The ANNALS of the American Academy of political and social science. 2023, Vol. 708, N 1, P. 137–163. DOI: https://doi.org/10.1177/00027162241228952
20. Druckman J.N., Gubitz S.R., Levendusky M.S., Lloyd A.M. How incivility on partisan media (De)Polarizes the electorate. The Journal of politics. 2019, N 81 (1), Р. 291– 295. DOI: https://doi.org/10.1086/699912
21. Esteban J.-M., Ray D. On the measurement of polarization. Econometrica. 1994, N 62 (4), Р. 819–851. DOI: https://doi.org/10.2307/2951734
22. Estrada M.S., Juarez Y., Pina-Garcia C.A. Toxic social media: affective polarization after feminist protests. Social media and society. 2022, Vol. 8, N 2, P. 1–12. DOI: https://doi.org/10.1177/20563051221098343
23. Gandhi A., Ahir P., Adhvaryu K., Shah P., Lohiya R., Cambria E., Poria S., Hussain A. Hate speech detection: a comprehensive review of recent works. Expert systems. 2023, Vol. 41, N 8, P. 1–24. DOI: https://doi.org/10.1111/exsy.13562
24. Gerber A., Green D. Misperceptions about perceptual bias. Annual review of political science. 1999, N 2 (1), Р. 189–210. DOI: https://doi.org/10.1146/annurev.polisci.2.1.189
25. Gomez R., Gibert J., Gomez L., Karatzas D. Exploring hate speech detection in multimodal publications. In: Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision. 2020, Р. 1470–1478.
26. Graham M.H., Svolik M.W. Democracy in America? Partisanship, polarization, and the robustness of support for democracy in the United States. American political science review. 2020, N 114 (2), Р. 392–409. DOI: https://doi.org/10.1017/S0003055420000052
27. Green D., Palmquist B., Schickler E. Partisan hearts and minds: political parties and social identities of voters. Yale: Yale University Press, 2002, 266 p. Greene S. Understanding party identification: a social identity approach. Pollical psychology. 1999, N 20, Р. 393–403. DOI: https://doi.org/10.1111/0162-895X.00150
28. Harel T.O., Jameson J.K., Maoz I. The normalization of hatred: identity, affective polarization, and dehumanization on Facebook in the context of intractable political conflict. Social media and society. 2020, N 6 (2), P. 1–10. https://doi.org/10.1177/2056305120913983
29. Harel T.O., Nir N., Vandermeulen D., Maoz I., Halperin E. A threat to cohesion: intragroup affective polarization in the context of intractable intergroup conflict. Journal of conflict resolution. 2024, Vol. 0 (0), P. 1–27. https://doi.org/10.1177/00220027241247033
30. Husunbeyi Z.M., Akar D., Ozgur A. Identifying hate speech using neural networks and discourse analysis techniques. In: Adebayo K. (ed.). Proceedings of the first workshop on language technology and resources for a fair, inclusive, and safe society within the 13-th language resources and evaluation conference. Paris: European language resources associate, 2022, P. 32–41.
31. Isenberg D.J. Group polarization: A critical review and meta-analysis. Journal of personality and social psychology. 1986, N 50, Р. 1141–1151. DOI: https://doi.org/10.1037/0022-3514.50.6.1141
32. Iyengar S., Sood G., Lelkes Y. Affect, not ideology: a social identity perspective on polarization. Public opinion quarterly. 2012, Vol. 76, N 3, P. 405–431. DOI: https://doi.org/10.1093/poq/nfs038
33. Iyengar S., Lelkes Y., Levendusky M., Malhotra N., Westwood S.J. The origins and consequences of affective polarization in the United States. Annual review of political science. 2019, N 22 (1), Р. 129–146. DOI: https://doi.org/10.1146/annurevpolisci-051117-073034
34. Jahan M.S., Oussalah M. A systematic review of hate speech automatic detection using natural language processing. Neurocomputing. 2023, Vol. 546, P. 1–30. DOI: https://doi.org/10.1016/j.neucom.2023.126232
35. Johnston R., Manley D., Jones K. Spatial polarization of presidential voting in the United States, 1992–2012: The “Big Sort” revisited. Annals of the American association of geographers. 2016, N 106 (5), Р. 1047–1062. DOI: https://doi.org/10.1080/24694452.2016.1191991
36. Kirkizh N., Ulloa R., Stier S., Pfeffer J. Predicting political attitudes from web tracking data: a machine learning approach. Journal of information technology and politics. 2024, N 21 (4), Р. 564–577. DOI: https://doi.org/10.1080/19331681.2024.2316679
37. Korgunyuk Y.G. The structure of electoral divisions in the 2011–2012 election cycle and possible scenarios for the development of the situation. Politiya. 2012, N 3, Р. 84–99. DOI: https://doi.org/10.30570/2078-5089-2012-66-3-84-99 (In Russ.)
38. Kruchinskaya E.V. Affective political polarization: proposals for the operationalization of the concept through the assessment of the language of hostility in social media. Information society. 2023, N 3, Р. 97–107. (In Russ.)
39. Kurganskaia E., Stepanova N. Identification of “toxicity” in social networks based on the semantic proximity criterion. Philology. Theory and practice. 2024, N 17, Р. 1596–1603. DOI: 10.30853/phil20240231 (In Russ.)
40. Lelkes Y., Westwood S.J. The Limits of partisan prejudice. Journal of politics. 2017, N 79 (2), Р. 485–501. DOI: https://doi.org/10.1086/688223
41. Malinova O.Y. Changing institutional conditions of production and competition of political ideas in Russia: from the 1990s to the 2010s. In Yarskaya-Smirnova E.R., Romanov P.V. (eds.). Public sphere: theory, methodology, case study. Moscow: OOO “Variant”: TSPGI, 2013, Р. 55–74. (In Russ.)
42. Mason L., Notes A.A. Cross-cutting calm: how social sorting drives affective polarization. Public opinion quarterly. 2016, Vol. 80, N S1, P. 351–377. DOI: https://doi.org/10.1093/poq/nfw001
43. Mason L., Wronski J. One tribe to bind them all: how our social group attachments strengthen partisanship. Political psychology. 2018, Vol. 39, N S1, P. 257–277. DOI: https://doi.org/10.1111/pops.12485
44. Moscovici S., Zavalloni M. The group as a polarizer of attitudes. Journal of personality and social psychology. 1969, N 12 (2), Р. 125–135.
45. Nezi P. A tale of two crises: affective polarization in Greece. Frontiers in political science. 2024, N 6, Article 1256199. DOI: https://doi.org/10.3389/fpos.2024.1256199
46. O’Reilly C., Maher P.J., Smith E.M., MacCarron P., Quayle M. Social identity emergence in attitude interactions and the identity strengthening effects of cumulative attitude agreement. European journal of social psychology. 2023, N 54, Р. 97–117. DOI: https://doi.org/10.1002/ejsp.3000
47. Olteanu A., Castillo C., Boy J., Varshney K. The Effect of Extremist Violence on Hateful Speech Online. In Proceedings of the Twelfth International AAAI conference on web and social media (ICWSM 2018). 2018, Vol. 12, N 1, P. 221–230. DOI: https://doi.org/10.1609/icwsm.v12i1.15040
48. Orr L.V., Flower A., Huber G.A. Is affective polarization driven by identity, loyalty, or substance? American journal of political science. 2023, Vol. 67, N 4, P. 948–962. DOI: https://doi.org/10.1111/ajps.12796
49. Petrov A., Akhremenko A.S., Zheglov S.A., Kruchinskaia E.V. Is network structure important for protest mobilization? Findings from agent-based modeling. Monitoring obshchestvennogo mneniya: ekonomichekie i sotsial'nye peremeny. 2021, N 6, Р. 226–253. DOI: https://doi.org/10.14515/monitoring.2021.6.2021 (In Russ.)
50. Philippov I.B. Quantitative textual characteristics as a factor of success in promoting publications within the framework of protest communication on social networks. Outlines of global transformations: politics, economics, law. 2020, Vol. 13, N 2, P. 249–268. DOI: https://doi.org/10.23932/2542-0240-2020-13-2-13 (In Russ.)
51. Philippov I.B. The “Moscow case” as a factor of protest communication activity in the social network “VK”. RUDN Journal of political science. 2022, Vol. 24, N 3, P. 530– 544. DOI: https://doi.org/10.22363/2313-1438-2022-24-3-530–544 (In Russ.)
52. Platonov E.N., Rudenko V.Yu. Identification and classification of toxic statements using machine learning methods. Modeling and data analysis. 2022, N 12 (1), Р. 27–48. DOI: https://doi.org/10.17759/mda.2022120103 (In Russ.)
53. Pronoza E., Panicheva P., Koltsova O., Rosso P. Detecting ethnicity-targeted hate speech in Russian social media texts. Information processing and management. 2021, N 58 (6), Article 102674.
54. Rosenberg M., Schooler C., Schoenbach C., Rosenberg F. Global self- esteem and specific self-esteem: different concepts, different outcomes. American sociological review. 1995, Vol. 60, N 1, Р. 141–156. DOI: https://doi.org/10.2307/2096350
55. Rosler N. Not as simple as that: how leaders faced the challenges of pursuing the peace process in Northern Ireland. Peace and conflict: Journal of peace psychology. 2016, N 22 (2), Р. 177–180. DOI: https://doi.org/10.1037/pac0000122
56. Sartori G. Parties and party systems: a framework for analysis. Cambridge: Cambridge University Press, 1976, Vol. 1, 390 p.
57. Schedler A. Rethinking political polarization. Political science quarterly. 2023, N 138, Р. 335–359. DOI: https://doi.org/10.1093/psquar/qqad038
58. Schmidt A., Wiegand M. A survey on hate speech detection using natural language processing. In: Ku L.-W., Li Ch.-T. (eds). Proceedings of the fifth international workshop on natural language processing for social media. Valencia: Association for computational linguistics, 2017, Р. 1–10. DOI: https://doi.org/10.18653/v1/W17-1101
59. Siegel D.A. Social networks and collective action. American journal of political science. 2009, N 53 (1), Р. 122–138.
60. Simmel G. Conflict and the web of group affiliations. New York: The Free Press, 1956, 208 p.
61. Smetanin S. Toxic comments detection in Russian. In: Selegey V. (ed.). Computational linguistics and intellectual technologies: proceedings of the international conference “Dialogue 2020”. Moscow: Publishing House of RSSU, 2020, P. 1149–1159.
62. Smith L.G.E., Thomas E.F., Bliuc AM. Polarization is the psychological foundation of collective engagement. Communications psychology. 2024, Vol. 2, N 1, Article 41. DOI: https://doi.org/10.1038/s44271-024-00089-2
63. Stukal D.K., Akhremenko A.S., Petrov A.P. Affective political polarization and hate speech: are they made for each other? RUDN Journal of political science. 2022, Vol. 24, N 3, P. 480–498. (In Russ.)
64. Stukal D.K., Belenkov V.E., Philippov I.B. Methods of data science in political research: analysis of protest activity in social networks. Political Science. 2021, N 1, P. 46–75. DOI: https://doi.org/10.31249/poln/2021.01.02 (In Russ.)
65. Tajfel H., Turner J.C. An integrative theory of intergroup conflict. In Austin W.G., Worchel S. (eds.). The social psychology of intergroup relations, Monterey, CA: Brooks / Cole, 1979, Р. 33–37.
66. Theelen M., Bohm R. The conflict-cooperation effect persists under intragroup payoff asymmetry. Group processes and intergroup relations. 2021, N 24 (5), Р. 815–835.
67. Thomas E.F., McGarty C., Mavor K. Group interaction as the crucible of social identity formation: a glimpse at the foundations of social identities for collective action. Group process and intergroup relations. 2016, N 19, 137–151.
68. Törnberg P., Andersson C., Lindgren K., Banisch S. Modeling the emergence of affective polarization in the social media society. PloS ONE. 2021, N 16 (10), Article e0258259. DOI: https://doi.org/10.1371/journal.pone.0258259
69. Tucker J.A., Guess A., Barberá P., Vaccari C., Siegel A., Sanovich S., Stukal D., Nyha B. Social media, political polarization, and political disinformation: a review of the scientific literature. SSRN electronic journal. 2018, P. 1–66. DOI: https://doi.org/10.2139/ssrn.3144139
70. Vartanova E. Gladkov A., Dunas D. On representation of conflict in modern academic discourse. Online media and global communication. 2022, N 1 (4), Р. 794–814. DOI: https://doi.org/10.1515/omgc-2022-0063
71. Webster S., Abramowitz A. The Ideological Foundations of Affective Polarization in the US Electorate. American Politics Research. 2017, N 45, Р. 621–647. DOI: https://doi.org/10.1177/1532673X17703132
72. Zingher J.N., Flynn M.E. From on high: the effect of elite polarization on mass level attitudes and behaviors, 1972-2012. British journal of political science. 2018, Vol. 48, N 1, P. 23–45. DOI: https://doi.org/10.1017/S0007123415000514
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