A scalable machine learning approach for measuring violent and peaceful forms of political protest participation with social media data

• DOI: 10.1371/journal.pone.0212834
• Publication Date: 2019-03-19T13:35:08Z
• Authors: Lefteris Jason An...; Jake Ryland Williams
• Keywords: Political Communication

In this paper, we introduce a scalable machine learning approach accompanied by open-source software for identifying violent and peaceful forms of political protest participation using social media data. While protests are statistically rare events, they often shape public perceptions movements. This is, in part, due to the extensive disproportionate coverage which receives relative participation. past, when small number conglomerates served as primary information source about movements, viewership advertiser demands encouraged news organizations focus on Consequently, much our knowledge is derived from data collected protests, while less known protest. Since early 2000s, digital revolution shifted attention away traditional sources toward current events. This, along with developments allow us collect analyze relevant participation, present unique opportunities expand through