Abstract
This study investigates the regional determinants of collective action in the era of “American
Resistance.” Drawing on a new dataset from “Count Love”—a machine learning tool that collects
data on protest events, timing, location, and number of attendees—we explore the regional
determinants of collective action in the first three years following President Trump’s election. In
particular, we investigate how socio-economic factors, political partisanship and demographic
composition of states affect the rate of protest events and protest participants. We also examine
the regional determinants of mass mobilization for specific causes, such as civil rights, anti-gun
violence, compassionate immigration policies, and climate change. Negative binomial regression
results demonstrate that states with higher economic growth, more democratic political
partisanship, and greater organizational capacity to police and contain mobilization witnessed
more protest events.
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