Computational Social Science Forum — From Ivory Tower to Ivory Bridge: Applications and Lessons Learned in Public Computational Social Science

CSS Training Program

October 19, 2021
4:00pm to 5:00pm
Virtual Participation


Berkeley Computational Social Science Forum
Date: Tuesday, October 19, 2021
Time: 4:00-5:00 PM Pacific Time
Location: Virtual Participation – Register to attend via Zoom

From Ivory Tower to Ivory Bridge: Applications and Lessons Learned in Public Computational Social Science

Speaker: Tim Thomas, Berkeley CSSTP Research Training Lead, and Research Director, Urban Displacement Project
Abstract: Translating scholarship to social good is no small task. Beyond the research, it requires special tools, approaches, public engagement, and humility that are often not taught in academic courses. Drawing from three data science projects on eviction and displacement, Tim Thomas will discuss the basic ingredients, pedagogy, and hurdles for effective public scholarship. While most of these projects changed policy and public opinion, some outcomes were less than desirable and may have had a negative impact on communities. We will have an open discussion on what it takes to translate data science to the public sphere and how to navigate it appropriately. 

The Berkeley 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 for more information or if you are interested in presenting current research for an upcoming session.


Tim Thomas

Research Training Lead, Berkeley Computational Social Science Training Program

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.