文章基本信息

标题：Hashtags as structural elements of digital socio-political agenda: folksonomy analysis
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作者：Olga Malysheva ; Natalia Ryabchenko
期刊名称：SHS Web of Conferences
印刷版ISSN：2416-5182
电子版ISSN：2261-2424
出版年度：2020
卷号：88
页码：1-9
DOI：10.1051/shsconf/20208801025
语种：English
出版社：EDP Sciences
摘要：The situation of the recent months, associated with constitutional transformational changes and struggle with coronavirus spread, showed that civic communications outperform the government as regards the speed, directions and the scale of discursive fields generation. The digital socio-political agenda forms new socio-cognitive patterns of civic behavior, which leads to the development of constructive or destructive socio-political practices. The government needs innovational approaches and complex methods to conduct timely predictive analysis of socio-political sentiment. It is necessary to develop computational linguistics that allows for Data Science and relational sociology methods, as well as linguo-discursive analysis to be used in order to assess the current state of the digital socio-political agenda and identify the transformational vector of social action in the offline space. The article reports the results of the study of ‘Коронавирус’ digital socio-political agenda that was conducted through the use of graph visualization method, folksonomy and linguo-discursive analysis. The empirical base for the study comprises a bulk of network data retrieved from Twitter via API. The findings of the study prove that ‘Коронавирус’ digital socio-political agenda has significantly transformed and expanded within a 5 months’ period, with COVID-19 topic receiving twice as much attention from online users.