Social Data Research Fellowship


Focusing on social media datasets culled from Twitter, Reddit, and Youtube, this project takes a comparative approach to assessing the impact of the Covid-19 pandemic on political polarization and solidarity in the United States and the United Kingdom—two nations governed by populist leaders who initially denied the seriousness of the viral outbreak. It will examine public discourse surrounding the forthcoming US elections and the actualization of Brexit in the context of the pandemic. Under the mentorship of the principal investigators, at least two graduate student research teams will attend to the dialectics of solidarity and strife that are shaping contemporary political processes and animating social media movements in these two democracies. Working together, the researchers will develop an innovative methodology for evaluating the intersection between the pandemic and democratic discourse, using sentiment analysis jointly with user accounts’ meta-data to measure political cohesion and polarization. To situate the study of the social media landscapes in conversations about emerging best practices, two complementary research initiatives will be formed: a data-intensive training program for the graduate student researchers and a cross-disciplinary seminar series. The seminars will ground topic-specific inquiry in ethical reflections that are rooted in political economy, setting qualitative frames around methodological and ethical questions. Funding will underwrite this unique collaboration between two social science research infrastructures at UC Berkeley: D-Lab and Social Science Matrix. Outputs will include substantive research projects on the datasets, the training workshop and seminar series, and a white paper on the ethics of social media research.

Principal Investigator

Marion Fourcade

Professor of Sociology; Director of Social Science Matrix, University of California, Berkeley

The project represents a unique collaboration between UC Berkeley’s two social science research infrastructures: D-Lab, a hub for training in data-intensive social science, and Social Science Matrix, an incubator for cross-disciplinary social science research. The principal investigator, Marion Fourcade, professor of sociology and director of Matrix, has written extensively on digital technologies, algorithmic regulation, and social media. She is currently conducting a research project using computational methods to study the transformation of discursive practices during the European sovereign debt crisis. Fourcade's collaborator David Harding, professor of sociology and director of UC Berkeley's D-Lab, has extensive experience with the collection and analysis of large-scale administrative data using advanced statistical methods. He currently codirects an NIH-funded graduate training program in computational social science. D-Lab executive director Claudia von Vacano runs the D-Lab’s methods’ training program and is a computational scholar specializing in hate speech and social media data. Gregory Renard, a technologist specializing in natural language processing methods with more than 20 years’ experience in the private sector, will also serve as a project advisor.