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Protest and Power Struggles on Social Media: the Case of Black Lives Matter on Twitter

Social media platforms like Twitter and Facebook are integral tools for social movements to pursue their various causes. Yet we currently know little about how power circulates within the social media environments that emerge around social movements as they gain prominence. The research Dr. Deen Freelon will present examines two additional sets of Twitter-based constituencies that engage with the same issues as the Black Lives Matter movement (BLM): 1) a countermovement, which opposes BLM’s goals and/or actions; and 2) a bystander public, which stands outside BLM and may be open to persuasion in favor of or against it. One overarching question involving these three constituencies is: how does power circulate between them within the shared issue space provided by Twitter, and what factors contribute to the successful exercise of power in contested social media contexts? To answer these questions, he will present the results of two studies of BLM on Twitter, one published and one in progress. The first compares the three constituencies in terms of three theoretically-derived metrics of social media power and analyzes how these metrics relate to elite engagement with the issue of police brutality. The second takes as its key outcome variable something Dr. Freelon calls social opinion, by which he mean opinions on political issues expressed on social media. By distinguishing between social opinions about protesters, victims, and police, Dr. Freelon develops a fine-grained impression of the factors that account for how movements, countermovements, and bystander publics express themselves on contentious issues.

 

Dr. Deen Freelon is an associate professor in the School of Media and Journalism at the University of North Carolina at Chapel Hill. His research covers two major areas of scholarship: 1) political expression through digital media and 2) data science and computational methods for analyzing large digital datasets. He has authored or co-authored over 30 journal articles, book chapters, and public reports, in addition to co-editing one scholarly book. He has served as principal investigator on grants from the Knight Foundation, the Spencer Foundation, and the US Institute of Peace. He has written research-grade software to calculate intercoder reliability for content analysis (ReCal), analyze large-scale network data from social media (TSM), and collect data from Facebook (fb_scrape_public). He formerly taught at American University in Washington, DC.

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