Protest Event Data from Geolocated Social Media Content

10 September 2020, Version 1
This content is an early or alternative research output and has not been peer-reviewed at the time of posting.

Abstract

While it is understood that protester identity, violence, and emotions affect the size of protests, these concepts have proved difficult to measure at the protest-day level. Geolocated text and images from social media can improve these measurements. This advance is demonstrated on protests in Venezuela and Chile; it uncovers more protests in Venezuela and generates new measures in both countries. Moreover, the methodology generates daily city-day protest data in 107 countries containing 82.7% of the world’s population and 97.15% of its GDP. These multimodal protest event data complement existing event datasets, though countries’ population and income constrain the reach of any methodology.

Keywords

protests
collective action
chile
venezuela
social media
twitter
violence
repression
demographics
identity
emotions
gender
race
big data
computational social science

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