Digital spaces of network aggression
Muscovites ‘ perception of migrants
Bibliographic Data
| ID | 12977700 |
|---|---|
| Authors | María Pilgún (0000-0002-8948-7075, Institute of Linguistics, corresponding author), Наиля Габдрахманова (0000-0002-3441-5533, Peoples' Friendship University of Russia) |
| Year | 2020 |
| Volume | 12 |
| Issue | 3 |
| Pages | 237-261 |
| Publication date | 2020-09-01 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Russian Journal of Communication (JOURNAL) |
| Journal identifiers | ISSN: 1940-9427 • E-ISSN: 1940-9419 |
| Publisher | Taylor & Francis (PUBLISHER • GB) |
| DOI | 10.1080/19409419.2020.1850088 |
| OpenAlex | W3111249573 |
| Language | EN |
| References cited | 32 |
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
Artificial neural network · Data science · Logistic function · Logistic regression · Machine learning · Perception · Predictive analytics · Task (project management · Computer Science · Engineering · Migration, Refugees, and Integration · Psychology · Social Media and Politics · Sociopolitical Dynamics in Russia · Artificial Intelligence
Genes, Mind, and Culture
Representation of Women in News and Photos
Images of Immigrants and Refugees in Western Europe
Human Rights, Migration, and Social Conflict
Agent-Based Modeling of Social Conflict
Political Effects of the Internet and Social Media
The state of the nation
Political protest Italian-style
A taxonomy for measuring the success of open source software projects
Extended infomercials” or ”Politics 2.0”? A study of Swedish political party Web sites before, during and after the 2010 election
Comparative Analyses of Public Attitudes Toward Immigrants and Immigration Using Multinational Survey Data
In the name of the nation
Ultra-Nationalism and hate crimes in Contemporary Russia, The 2004-2006 Annual Reports of Moscow’s Sova Center
Norwegian Parties and Web 2.0
Voice and community in the 2015 refugee crisis
Television and anti-immigrant sentiments
From the air to the ground
Facebooking for Good
Social Ties and Generalized Trust, Online and in Person
Changing attitudes toward immigration in Europe, 2002–2007
A Global Hypothesis for Women in Journalism and Mass Communications
Communication and Conflict Studies
Digital Spaces of Civic Communication
Public Attitudes Toward Immigration
Investigating the representation of migrants in the UK and Italian press
| Citation velocity | historical |
|---|---|
| Highly cited | No |