In the situation of a shrinking field of public politics and a crisis of political trust, citizens may seek an alternative arena for presenting their own point of view. The social Internet space serves as a virtual projection of public contradictions and acts as an arena for the presentation and confrontation of political interests. At the same time, the increasing state presence in virtual space and the growing trust to online sources of information make social media an important channel for promoting certain patterns of political interpretations. The aim of this paper is to analyse the reactions of social media users to discover their attitudes towards the main narratives of contemporary identity politics of the Russian state. We used the Topic modelling method to study citizens’ reactions to various aspects of state identity politics. The total number of comments in the collected database is 8,023 (09/2022-09/2023). In almost all the identified topics we can note the polarity of citizens’ opinions, examples of which are given in the article. However, there are a few topics where the users’ opinion is quite consolidated; for example, the image of the Crimean bridge on the cover of new textbooks was widely supported in comments, while the topic of traditional values, on the contrary, evokes negative feelings and shows “public tiredness”. Despite the limitations described in the conclusion of the article, the study demonstrates the high potential of applying the method of topic modelling to the analysis of the reactions of social media users. © 2024, LLC Scientific Industrial Enterprise "Genesis. Frontier. Science". All rights reserved.
Язык оригиналарусский
Страницы (с-по)358-375
Число страниц18
Журнал GALACTICA MEDIA: JOURNAL OF MEDIA STUDIES
Том6
Номер выпуска3
DOI
СостояниеОпубликовано - 30 сен 2024

    Области исследований

  • Effectiveness of Identity Politics, Identity Politics, Memory Politics, Network Research, Political Identity, Social Network Analysis, Social Network Users, Social Network “VK”, State Identity Politics, Topic Modelling Method

ID: 126218978