Political Mobilization at the Time of Coronaphobia: Big-Data Analysis of the Emotional Effects of the Pandemic

The COVID-19 pandemic was characterised by the intensification of inter-group violence and xenophobia (UNISEF 2020, Crisis Group 2020, UN 2020, ISS 2020), which— according to the literature on the psychology of pandemics—was en evolutionary response to the new disease that spreads during contacts with out-group members (Gordon et a. 2020, Troisi 2020). As such, the growth of interpersonal distrust and intensification of pre-exiting ethnic tensions are behavioural outcomes of pandemics. In-spite of coronaphobia, however, the COVID-19 pandemic brought with itself an unprecedented political mobilization worldwide both in authoritarian and democratic regimes. How did such mobilization become possible at the time of the growing interpersonal distrust and the fear of contamination that increased the costs of participation and should have made the collective action more difficult? The rapidly growing literature on mobilization during the COVID-19 has explained this phenomena by the grievance theory (Berman et al. 2020, Gutiérrez-Romero 2020). This paper adopts an alternative approach by examining the role of emotions in political mobilization. The analysis is based on a unique dataset of abut 10 million tweets related to COVID-19 generated by users in 16 former British colonies in Asia, Africa, and the Caribbean to test empirically the relative importance of economic grievances vis-a-vis emotions triggered by COVID that enabled political entrepreneurs to channel anxieties related the pandemic to challenge the incumbents grip on power. Each tweet was assigned emotional score using a cutting edge machine learning algorithm and was linked to the location of tweeter users. These data were merged with the ACLED data on political violence and hazard-ratio model was estimated to examine the importance of both positive and negative emotions on political protests and riots in urban areas. This study advances the scholarly debate on the role of emotions in political protests in three respects. First it applies a novel methodology based on big-data and sentiment analysis that allows to conduct cross-country and cross-regional comparison of the role of emotions in political process, this is usually is not feasible in the experimental design. Second, it allows to test for the relative importance of positive and negative emotions in a singe study. Third it departs from the prospect theory framework that has dominated the psychology paradigm (Halperin 2016, Brader and Marcus 2013, Lerner et al. 2015, Jasper 1998 & 2018) and offers an explanation that integrates the theory of emotional contagion (Ross 2015, Hutchison 2016) with game-theoretic approaches to emotional mobilization (Petersen 2011).