The outbreak of the COVID-19 pandemic has led to an upsurge of protests. The emergence of civil resistance movements is often associated with various conditions of social systems. The analysis of social systems also shows the importance of considering the behaviour time scale and in particular slow-fast dynamics. The fine-grained datasets of the sudden and dramatic disruptive force of the pandemic can be used to better grasp the different dynamics of this social phenomenon.

This paper proposes a holistic approach to explore the relationship between societal conditions and the emergence of protests in the context of the COVID-19 pandemic. First, a literature survey was performed to identify key conditions that lead to the emergence of protests. These conditions and underlying relations have been captured in a causal loop diagram to conceptualise the emergence of civil resistance as a result of intertwined dynamics. A data set is constructed for quantitative analysis.

By means of statistical and computational modelling we conduct a quantitative analysis in which we compare the protest dynamics of 27 countries during the pandemic. We construct a systems dynamics model to test the explanatory value of different theoretical models on causal relationships, as our results demonstrate a strong need for other modelling approaches that better capture the complexity and underlying dynamics of protests.

Our analysis suggests that while models could improve their understanding of when civil resistance might happen by incorporating variables that analyse fast changes in social systems, incorporating variables that analyse slow developments of structural conditions might further improve estimates for the severity of such outbreaks.

K. van der Zwet, A. I. Barros, T. M. van Engers, P. Sloot, Emergence of protests during the COVID-19 pandemic: quantitative models to explore the contributions of societal conditions, Humanities and Social Sciences Communications 9 (2022) 68.