SODAS Lecture: How State and Protester Violence Affect Protest Dynamics

Title:

How State and Protester Violence Affect Protest Dynamics.

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 article 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 re- quires 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.

Bio:

Professor Zachary Steinert-Threlkeld is an Associate Professor of Public Policy at UCLA’s Luskin School of Public Affairs.  His research seeks to understand protest dynamics using natural language processing, computer vision, and large-scale simulations.  He has studied protests around the world, including the Arab Spring, East Asia, and the Americas.  His newest work looks at evasion of the Great Firewall in China during COVID-19, signalling on social media during the Syrian civil war, how state violence can make protests smaller or larger, and the effect of social media taxation.  His work has been published in the American Political Science Review, Journal of Politics, Political Analysis, Proceedings of the National Academy of Sciences, and World Development and received coverage from Al-Jazeera, The Atlantic, Business Insider, The Economist, The New York Times, Scientific American, and WIRED (2).

The lecture will be streamed on Zoom via the following link: https://ucph-ku.zoom.us/j/62059888624 (Meeting-ID 620 5988 8624)