Digital spaces of network aggression: Muscovites ‘ perception of migrants

The paper presents the analysis of speech perception and of the specific nature of communication between migrants and residents of Moscow, as reflected in the digital environment. The main focus is on conflictogenic digital zones, as well as methods for predicting and preventing conflicts. The development of algorithms to make predictions about users’ possible actions, the occurrence and prevention of conflicts is an important task of interdisciplinary research. The goals of research were achieved based on the analysis of social media data. Neural network modeling, statistical analysis, and differential equations were used as research methods. In mathematical modeling, three types of models were built: an equation of linear regression, as well as logistic and type-epidemiological mathematical models. The study showed that the use of parallel models using differential equations, mathematical statistics and neural network technology to determine the dynamics of aggressive online activity, in particular, to analyze users’ perception of conflict situations related to the topic of migrants, makes it possible to correctly analyze conflict zones in the development of a modern metropolis, to increase the effectiveness of research methods and predictive analytics of the development of social tension. © 2020 Informa UK Limited, trading as Taylor & Francis Group.

Authors
Pilgun M.1 , Gabdrakhmanova N. 2
Publisher
Bellwether Publishing, Ltd.
Number of issue
3
Language
English
Pages
237-261
Status
Published
Volume
12
Year
2020
Organizations
  • 1 Russian Academy of Sciences, Institute of Linguistics, Moscow, Russian Federation
  • 2 Peoples Friendship University of Russia (RUDN University), Moscow, Russian Federation
Keywords
differential equations; mathematical statistics; neural network model; Social media data; speech perception
Date of creation
20.04.2021
Date of change
20.04.2021
Short link
https://repository.rudn.ru/en/records/article/record/72820/
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