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From Facebook to the Streets: Russian Troll Ads and Black Lives Matter Protests

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Title:From Facebook to the Streets: Russian Troll Ads and Black Lives Matter Protests
Authors:Etudo, Ugo
Yoon, Victoria Y
Yaraghi, Niam
Keywords:Text Mining in Big Data Analytics
Collaboration Systems and Technologies
Trolling, Topic Models, Russia, Election, Facebook
Date Issued:08 Jan 2019
Abstract:Online trolling is typically studied in the IS literature as an uncoordinated, anarchic activity. Coordinated, strategic online trolling is not well understood despite its prevalence on social media. To shed light on this prevailing activity, the present study examines the proposition that coordinated online trolling is timed to leverage macro societal unrest. In testing this proposition, we analyzes the dynamics of the Russian State’s coordinated trolling campaign against the United States beginning in 2015. Using the May 2018 release of all Russian Troll Facebook advertisements, this study constructs a topic model of the content of these ads. The relationship between ad topics and the frequency of Black Lives Matter protests is examined. We argue that the frequency of Black Lives Matter protests proxies for civil unrest and divisiveness in the United States. The study finds that Russian ads related to police brutality were issued to coincide with periods of higher unrest. This work also finds that during periods of relative calm (evidenced by lower frequency of protests) Russian ads were relatively innocuous.
Pages/Duration:8 pages
Rights:Attribution-NonCommercial-NoDerivatives 4.0 International
Appears in Collections: Text Mining in Big Data Analytics

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