Modeling revolutions in networked societies: learning from the Tunisian spring
Daniel Aguilar-Vel\'azquez, Denis Boyer, Robert Boyer

TL;DR
This paper models how localized events in networked societies can trigger large-scale revolutions, highlighting the role of social ties, fear, and repression through a complex systems approach.
Contribution
It introduces a formal network model inspired by complex systems theory to explain the conditions leading to revolutions, including phase transitions and hysteresis effects.
Findings
Revolutions can be triggered by localized events in social networks.
The model shows a phase transition at a critical threshold of social tension.
Repression needs to be increased beyond initial levels to regain control after mobilization.
Abstract
Economic competition and deregulation have led to a polarization of societies between a small, increasingly powerful elite and a majority of socially excluded individuals, marginalized and unconnected to political representations. This is the breeding ground for protest movements, relayed by local ties and amplified by social networks. Based on the characteristics revealed by socio-economic research into the Arab revolutions of the 2010s, this article proposes a formalization inspired by the theory of complex systems. We discuss the conditions under which an initial localized event - for example, the suicide of a street vendor condemned to ruin in a small Tunisian town - can trigger an explosion of the number of opponents to the regime, typical of a revolutionary episode. We consider a network model of agents and oppressors where pair interactions are controlled by a fear parameter, or…
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Taxonomy
TopicsOpinion Dynamics and Social Influence · Political Conflict and Governance · Ecosystem dynamics and resilience
