Detection of Induced Activity in Social Networks: Model and Methodology

Dmitrii Gavra, Ksenia Namyatova and Lidia Vitkova
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Dmitrii Gavra: Department of Public Relations in Business, St. Petersburg State University, 7-9 Universitetskaya Embankment, 199034 St. Petersburg, Russia
Ksenia Namyatova: Department of Public Relations in Business, St. Petersburg State University, 7-9 Universitetskaya Embankment, 199034 St. Petersburg, Russia
Lidia Vitkova: St. Petersburg Federal Research Center of the Russian Academy of Sciences (SPC RAS), 39, 14th Line V.O., 199178 St. Petersburg, Russia

Future Internet, 2021, vol. 13, issue 11, 1-13

Abstract: This paper examines the problem of social media special operations and especially induced support in social media during political election campaigns. The theoretical background of the paper is based on the study fake activity in social networks during pre-election processes and the existing models and methods of detection of such activity. The article proposes a methodology for identifying and diagnosing induced support for a political project. The methodology includes a model of induced activity, an algorithm for segmenting the audience of a political project, and a technique for detecting and diagnosing induced support. The proposed methodology provides identification of network combatants, participants of social media special operations, influencing public opinion in the interests of a political project. The methodology can be used to raise awareness of the electorate, the public, and civil society in general about the presence of artificial activity on the page of a political project.

Keywords: network operations; network combatants; social bots; social network analysis; induced activity; induced activity detection; election campaigns (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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