COMPUTATIONAL SOCIAL SCIENCE WORKSHOP
Abstract: How do state and protester violence affect whether protests grow or shrink? Previous research finds conflicting results for how violence affects protest dynamics. This paper argues that expectations and emotions should generate an n-shaped relationship between the severity of state repression and changes in protest size the next day. Protester violence should reduce the appeal of protesting and increase the expected cost of protesting, decreasing subsequent protest size. Since testing this argument requires precise measurements, a pipeline is built that applies convolutional neural networks to images shared in geolocated tweets. Continuously valued estimates of state and protester violence are generated per city-day for 24 cities across five countries, as are estimates of protest size and the age and gender of protesters. The results suggest a solution to the repression-dissent puzzle and join a growing body of research benefiting from the use of social media to understand subnational conflict.
Zachary C. Steinert-Threlkeld is an assistant professor of public policy at the University of California, Los Angeles’ Luskin School of Public Affairs and has a Ph.D. in political science from the University of California, San Diego. He uses computational methods to study protest dynamics, with a particular interest in how social networks affect individuals’ decision to protest. Text analysis has studied mobilization during the Arab Spring; information warfare in Ukraine; and activists’ online strategies. Work with images measures how violence, social cleavages, and free riding affect protest dynamics. Other work includes simulations of protest diffusion and studying how governments attempt to influence individuals’ online behavior.
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This workshop is cosponsored by the Center for the Study of American Politics (CSAP) and the Yale School of Management (SOM) with support from the Initiative for Leadership and Organization at SOM.