Political Framing and its Propagation in Media
We propose to investigate political framing in digital media, using a novel combination of computational linguistics and machine learning tools to investigate key areas crucial for preserving democracy in the post-industrial world. These include the ability of governments or non-state actors to influence or undermine the democratic process through propaganda or agenda-setting, the way new media distinguish (or don’t distinguish) subjective opinions from objective data, how minority and majority groups are portrayed, and the way partisan frames emerge and diffuse. Our research makes use of data spanning different media, time periods, and content creators (e.g., journalists, ordinary citizens, politicians), including our own corpus of 50 billion news media articles and social media posts, as well as historical collections of media in multiple languages. Our project has the potential to significantly advance our understanding of the effect of cyber media on the political landscape as well as developing novel computational tools to help detect these latent influences on media.
Pan, J. “How Market Dynamics of Domestic and Foreign Social Media Firms Shape Strategies of Internet Censorship.” Problems of Post-Communism Vol. 64 , Iss. 3-4,2017
Srijan Kumar, William L. Hamilton, Jure Leskovec, and Dan Jurafsky. "Community Interaction and Conflict on the Web." Proceedings of the 2018 World Wide Web Conference (WWW '18). International World Wide Web Conferences Steering Committee, Republic and Canton of Geneva, Switzerland, 933-943. 2018. DOI: https://doi.org/10.1145/3178876.3186141