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News
May 22, 2026
HSE Graduates AI Project Wins at TECH & AI Awards
Daria Davydova, graduate of the HSE Graduate School of Business and Head of the AI Implementation Unit at the Artificial Intelligence Department of Alfa-Bank, received a prize at the TECH & AI Awards. She was awarded for the best AI solution for optimising business processes. The winners were determined as part of the VII Russian Summit and Awards on Digital Transformation (CDO/CDTO Summit & Awards).
May 20, 2026
HSE University Opens First Representative Office of Satellite Laboratory in Brazil
HSE University-St Petersburg opened a representative office of the Satellite Laboratory on Social Entrepreneurship at the University of Campinas in Brazil. The platform is going to unite research and educational projects in the spheres of sustainable development, communications and social innovations.
May 18, 2026
The 'Second Shift' Is Not Why Women Avoid News
Women are more likely than men to avoid political and economic news, but the reasons for this behaviour are linked less to structural inequality or family-related stress than to personal attitudes and the emotional perception of news content. This conclusion was reached by HSE researchers after analysing data from a large-scale survey of more than 10,000 residents across 61 regions of Russia. The study findings have been published in Woman in Russian Society.

 

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Modeling Street Protests: Turnout Dynamics and Government Response

.
Petrov A., Zheglov S., Kruchinskaia E., Akhremenko A.

In this paper, we present a new agent-based and network-based model of protest campaigns in the presence of repression from the authorities. It includes both rational and socio-psychological factors in the behavior of the protesters. An analytical study of the simplified form of the model (without a network structure) leads to two main findings. First, a protest campaign unfolds successfully, reaching a significant number of participants, only if it overcomes a certain turnout threshold before the start of repression. Second, there exists a critical level of repression's severity, at which the protest campaign will not survive, regardless of the initial number of participants. This threshold occurs when individuals have a relatively high level of risk aversion. A computational experiment has shown that its existence and value do not depend on the network topologies, traditionally explored in the literature - namely Watts-Strogatz, Barabási-Albert, and regular graph. Yet an experiment has also demonstrated that this “repression barrier” can be overcome by more specialized network structures. One of them is the special version of the so-called STAR topology, when the most active and the only agent is linked with all other agents, allows the protest campaign to survive at any rate of repression.

Language: English
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Keywords: repressioncomputational modelpolitical protestagent-based model

In book

14th International Conference Management of large-scale system development (MLSD)
IEEE Xplore, 2021.
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