The research is aimed at building a methodology detection of one of the new and extremely destructive social mechanisms for mobilizing political protest in the information and network society, which is the mechanism for mediating local incidents. Based on algorithms artificial intelligence it is planned to develop a methodology and software for diagnosing local incidents in social network. If this methodology is used, it will be possible to study a new and extremely dangerous phenomenon, which is a mass mobilization of protest caused not by endogenous, but exogenous factors, in some cases inspired by external stakeholders, more strictly and correctly. A distinctive feature of the proposed approach is the possibility of developing an automated system based on specially developed algorithms for monitoring potentially dangerous local incidents for socio-political stability. In the work is received information about the functions and potential of various machine learning models. Is made conclusion about which models are the most optimal for analyzing messages about protest activity. The methodology proposed by the authors is promising for further research and development, because it makes it possible to convert text values into numeric values and to add a sign of the presence of a call to messages.
Original languageEnglish
Title of host publicationAdvances in Automation II - Proceedings of the International Russian Automation Conference, RusAutoConf 2020
Subtitle of host publicationroceedings of the International Russian Automation Conference, RusAutoConf2020, September 6-12, 2020, Sochi, Russia
EditorsAndrey A. Radionov, Vadim R. Gasiyarov
PublisherSpringer Nature
Pages468-478
Number of pages11
ISBN (Print)978-3-030-71118-4
DOIs
StatePublished - 2021
EventInternational Russian Automation Conference, RusAutoConf 2020 - Sochi, Russian Federation
Duration: 6 Sep 202012 Sep 2020

Publication series

NameLecture Notes in Electrical Engineering
Volume729 LNEE
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

ConferenceInternational Russian Automation Conference, RusAutoConf 2020
Country/TerritoryRussian Federation
CitySochi
Period6/09/2012/09/20

    Scopus subject areas

  • Industrial and Manufacturing Engineering

    Research areas

  • Information security, Machine learning models, Mediatization, Neural networks, Protest activity, Social networks, Word processing

ID: 85405381