This project was concluded in 2023.
Project information
Title
Predictors of political activism in social media and successful strategies of political mobilisation in online context
Doctoral student
Elizaveta Kopacheva
Supervisor
Per Strömblad
Assistant supervisor
Giangiacomo Bravo
Financier
Linnaeus University Centre for Data Intensive Sciences and Applications (DISA)
Timetable
1 July 2019–1 March 2024
Subject
Political science (Department of Political Science, Faculty of Social Sciences)
More about the project
The project is focused on the factors influencing people to participate in online activism and other online political activities, e.g. petition signing or contacting. Previous research has shown that internal political efficacy (i.e. the individual’s belief in oneself to influence political decision-making) is one of the main factors determining online political participation. In the meanwhile, only in Europe alone, more than half of the population is characterized as having low internal political efficacy. In such conditions, it is essential to stimulate online political participation.
The project aims to contribute to the research on political mobilisation. In particular, it is interesting to investigate what are the successful practices of political mobilisation/demobilisation in the online context. Case studies include demobilisation strategies carried out by Russian executives to reduce participation in online petition signing, and successful practices used by Russia's anti-landfill and international hashtag movements.
The main methods of research are dynamic network analysis and text mining. The project’s objectives include providing a framework for using complex data mining techniques to answer crosscutting questions of social science research.
The project is part of the research in the Linnaeus University Centre for Data Intensive Sciences and Applications (DISA), Computational Social Sciences (CSS) and Linnaeus University Research Group on Political Behavior, Opinion and Parties (LNU-POP) research groups.
