Online Protest and Repression in Authoritarian Settings

Aytalina Kulichkina (), Annie Waldherr () and Nanda Wijermans ()
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Nanda Wijermans: https://www.stockholmresilience.org/meet-our-team/staff/2012-10-18-wijermans.html

Journal of Artificial Societies and Social Simulation, 2026, vol. 29, issue 2, 4

Abstract: Digital spaces increasingly shape the dynamics of contemporary activism in authoritarian contexts, often complementing or even substituting physical protests. Social media have been particularly empowering by providing relatively safer means of expressing and amplifying grievances in networked environments. However, they have also enabled regimes and their supporters to engage in digital repression. Existing research highlights the need for exploring online protest-repression dynamics, which we address through an agent-based modeling approach. In this study, we integrate theoretical and empirical insights into online protest and repression in authoritarian settings to model social media interactions that can result in enduring campaigns or suppressed dissent. Our findings suggest that active protest expression on social media can positively contribute to ordinary users’ latent propensity to protest, even in highly authoritarian contexts and despite prevailing silence and repression. Conversely, when online protest expression is less visible, digital repression becomes more effective, even in low-authoritarian settings, as it heightens perceptions of successful suppression among ordinary users. We also find that repressors mobilize a small yet stable subset of ordinary users, which helps them reinforce silence across most scenarios, while the impact of voiced dissent quietly accumulates within those who are potentially ready to protest. Our model implementation provides a baseline for studying online protest and repression dynamics, contributing to the theoretical understanding of digital activism in authoritarian settings and offers insights for policymakers, activists, and social media stakeholders seeking to navigate, counter, and prevent digital repression.

Keywords: Protest; Repression; Social Media; Authoritarianism; Agent-Based Model (search for similar items in EconPapers)
Date: 2026-03-31
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