How State and Protester Violence Affect Protest Dynamics

07 May 2021, Version 3
This content is an early or alternative research output and has not been peer-reviewed at the time of posting.

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.

Keywords

social movements
repression
dissent
violence
social media
images
machine learning
convolutional neural network
Twitter
big data
repression-dissent
computer vision

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