Computational Social Science Forum
Date: Tuesday, September 14, 2021
Time: 4:00-5:00 PM Pacific Time
Location: Virtual Participation – Register to receive the schedule and access links
This first meeting of the Fall 2021 semester will be an orientation for new participants, for planning upcoming activities and to meet/greet the CSSTP Fellows.
The Computational Social Science Forum is an informal setting for the interdisciplinary exchange of ideas and scholarship at the intersection of social science and data science. Participants engage in a variety of activities such as presentations of work in progress, discussions and critiques of recent papers, introductions to new tools and methods, discussions around ethics, fairness, inequality, and responsible conduct of research, as well as professional development. This Forum is organized as part of the Computational Social Science Training Program, and weekly meetings are hosted by researchers from BIDS and D-Lab. The group welcomes social scientists and researchers with interests in data science methods and tools, and data scientists with applications or interests in public policy, social, behavioral, and health sciences. Participants include graduate students, postdocs, staff, and faculty, and members are encouraged to attend regularly in order to foster community around improving computational social science research, supporting the development and research of group members, and fostering new collaborations. Interested UC Berkeley community members are invited to use this registration form to receive the schedule and access links. Please contact css-t32@berkeley.edu for more information or if you are interested in presenting current research for an upcoming session.
Speaker(s)
Tim Thomas
Tim Thomas is a postdoctoral scholar and research director at the Urban Displacement Project specializing in urban sociology, demography, and data science. His research focuses on how neighborhood change, housing, and displacement affects household socioeconomic stratification and mobility by race and gender in the United States. His research at the UDP centers on developing an open-source neighborhood typology on displacement and gentrification as well as a national housing precarity risk model measured through the risk of eviction, displacement, unemployment, and COVID-19 infection. Tim is also the Principal Investigator for the Evictions Study, a multi-metropolitan analysis on the neighborhood drivers of eviction using census data and text mining court records. Tim's research agenda is marked by an intellectual foundation in policy-relevant research operationalized through civic and academic collaborations that address real-world problems and advances scholarly research. In 2019, his team's work on evictions provided empirical evidence that helped pass several tenant protections laws in Washington State and Baltimore City. In 2021, his research on evictions informed the CDC eviction moratorium and HUD strategies on data collection.
David J. Harding
David J. Harding is Professor of Sociology and Faculty Director of the D-Lab, which supports data-intensive research in the social sciences and humanities. Dr. Harding studies poverty and inequality, urban neighborhoods, education, adolescents and young adults, incarceration, and prisoner reentry. He uses both qualitative and quantitative methods. His current projects include the social and economic reintegration of former prisoners, the transition to adulthood after prison, the effects of incarceration on crime, employment, and health, and causal inference for contextual effects research.