Mathematical model of the social conflict representation: creation and testing on a corpus of texts

For citation: Nefedova Yu., Vartanova E.L., Anikina M.E. Mathematical model of the social conflict representation: creation and testing on a corpus of texts // Mediascope. 2024. 3. Available at: https://www.mediascope.ru/2870

© Yulia S. Nefedova

PhD in Engineering, Associate Professor at the Chair of Radio-Electronic Systems and Devices, Bauman Moscow State Technical University (Moscow, Russia), Head of the Scientific and Experimental Laboratory for Technical Tools in Journalism (Faculty of Journalism, Lomonosov Moscow State University (Moscow, Russia), yulja.nefedova@mail.ru

© Elena L. Vartanova

Academician of the Russian Academy of Education, Professor, Doctor of Philology, Dean of the Faculty of Journalism (Lomonosov Moscow State University), Head of the Chair of Media Theory and Economics, Lomonosov Moscow State University (Moscow, Russia), eva@smi.msu.ru

© Maria E. Anikina

PhD in Philology, Associate Professor at the Chair of Sociology of Mass Communications, Faculty of Journalism, Lomonosov Moscow State University (Moscow, Russia), maria-anikina@yandex.ru

Abstract

The study of thematic conflict in digital media environments is currently relevant. To analyze a large volume of text data automatically, a mathematical model based on neural algorithms was developed. The work examined the Arab-Israeli conflict of 2023. The initial data for the analysis were posts and comments to them on the Telegram social network. The resulting models show that the nature of the distribution of the number of comments fully corresponds to the nature of the distribution of the number of posts. In the period under review, the representation of the conflict can be divided into 3 phases. To study the conflict of messages, a speech mathematical model was developed. With its help, a detailed analysis of the tone of posts and comments on them was carried out for different subjects of the media space. It is shown that the representation of the Arab-Israeli conflict of 2023 in digital media does not affect the level of aggression of participants in the media space.

Keywords: social conflict, representation, mathematical model, neural network model, media.

Notes

Reyting Telegram-kanalov Рейтинг Telegram-каналов [TGStat. Telegram channel rating]. TGStat. Available at: https://tgstat.ru/ratings/channels (In Russian)

Monitoring SMI i sotssetey Мониторинг СМИ и соцсетей [Medialogy. Monitoring of media and social networks]. Medialogiya. Available at: https://www.mlg.ru/ (In Russian)

RIA Novosti. Available at: https://ria.ru/

TASS. Available at: https://tass.ru/

RBK [RBC]. Available at: https://www.rbc.ru/

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