Abstract
The paper analyzes speech markers and semantic concepts typical for patriotic and oppositional discourse in social networks. About 100 000 posts from Facebook, VKontakte, and LiveJournal were analyzed, and 35 000 most frequent speech markers were processed, of which 1800 markers were selected for analysis. The alternative method to TF–IDF metric for specific text markers identification is proposed. The features of oppositional discourse in comparison with the patriotic discourse were formulated. On the one hand, the analysis of sets of speech markers that characterize political groups allows us to understand social models and attitudes embedded in the discourse and the subsequent behavior of representatives of these groups. On the other hand, it is possible to extend a set of keywords for text search of a certain political orientation, based on the obtained results.
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References
Bally, S.: Language and Life. URSS, Moscow (2003)
van Dijk, T.: Discourse and Communication. Walter de Gryuter, Berlin (1985)
van Dijk, T.: News as Discourse. Hillsdale, NJ, Erlbaum (1988)
Eissa, M.: Polarized discourse in the news. Procedia Soc. Behav. Sci. 134, 70–91 (2014)
Fairclough, N.: Critical Discourse Analysis. The Critical Study of Language. Longman, London (1995)
Gonawela, J.: Studying political communication on Twitter: the case of small data. Curr. Opin. Behav. Sci. 18, 97–102 (2017)
Horvath, J.: Critical analysis of Obama’s political discourse. In: International Conference of Language, Literature and Culture in a Changing Transatlantic (2009)
Issers, O.: Communicative Strategies and Tactics of the Russian Language. URSS, Moscow (2008)
Kim, D., Seo, D., Cho, S., Kang, P.: Multi-co-training document classification using various document representations: TF-IDF, LDA, and Doc2Vec. Inf. Sci. (2018)
Lotman, Y.: The Semiosphere. Art-SPB, Saint-Petersburg (2010)
Makeeva, L.: Language, Ontology and Realism. Publishing House of the Higher School of Economics, Moscow (2011)
Manning, C., Raghavan, P., Schutze, H.: Scoring, term weighting, and the vector space model. In: Introduction to Information Retrieval. Cambridge University Press, New York, NY, USA (2008)
Monroe, B., Colaresi, M., Quinn, K.: Fightin’ words: lexical feature selection and evaluation for identifying the content of political conflict. Polit. Anal. 16(4), 372–403 (2008)
De Saussure, F.: Works on Linguistics. Progress, USSR (1977)
Shipilov, A.: Opposition “us–them” in sociocultural development. Philos. Leg. Thought: Alm. 5, 280–304 (2003)
Tsivyan, T.: Model of the World and its Linguistic Basis. URSS, Moscow (2009)
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The study has been funded by the Russian Academic Excellence Project “5–100”.
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Shcheglova, T., Gradoselskaya, G., Karpov, I. (2020). Methodology for Measuring Polarization of Political Discourse: Case of Comparing Oppositional and Patriotic Discourse in Online Social Networks. In: Bychkov, I., Kalyagin, V., Pardalos, P., Prokopyev, O. (eds) Network Algorithms, Data Mining, and Applications. NET 2018. Springer Proceedings in Mathematics & Statistics, vol 315. Springer, Cham. https://doi.org/10.1007/978-3-030-37157-9_15
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DOI: https://doi.org/10.1007/978-3-030-37157-9_15
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