The Computational Social Science Forum provides an informal setting for the interdisciplinary exchange of ideas and scholarship at the intersection of social science and data science. Our goal is to improve computational social science research, support the development and research of our members, and foster new collaborations. Weekly meetings are hosted by researchers from BIDS and D-Lab, and 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. We welcome social scientists researchers with interests in data science methods and tools, and data scientists with interests in public policy and the social, behavioral, and health sciences. Our participants include graduate students, postdocs, staff, and faculty, and members are encouraged to attend regularly in order to foster community.
This Forum was launched in Fall 2020 as part of the Computational Social Science Training Program, and interested UC Berkeley community members are invited to use this registration form to receive the schedule and access links. It is currently being organized by Dave Harding, Professor of Sociology and Faculty Director of D-Lab at UC Berkeley; Adam Anderson, BIDS Research Training Program Manager; and Douglas Guilbeault, Assistant Professor of Management of Organizations at the Berkeley Haas School of Business. Contact css-t32@berkeley.edu for more information. View previous events in the CSS Training Program video archive.
Spring 2021 Meetings
Computational Social Science Forum
Date: Weekly on Mondays starting on February 1, 2021
Time: 12:00-1:30 PM Pacific Time
Location: Virtual Participation
- March 8: CSS Forum: Strong ties and network search, Mathijs De Vaan, Berkeley Haas School of Business
- March 15: CSS Forum: Social network analysis and the missing data challenge, Martin Eiermann, UC Berkeley Sociology
- March 18: TADA-BSSR Webinar: Translating Domain Knowledge into Mechanistic Process Models: Illustrating the Need with a Just-in-Time Adaptive Intervention, Eric Hekler, UC San Diego; Misha Pavel, Northeastern University; Donna Spruijt-Metz, University of Southern California
- March 22: No meeting, Spring Break
- March 29: Pushing for Police Transparency by Tracking Police Misconduct, Julie Ciccolini, Director of Law Enforcement Accountability, NACDL
- April 5: CSS Forum: Using an online sample to estimate the size of an offline population, Dennis Feehan, Assistant Professor, Demography, UC Berkeley
- April 12: CSS Forum: Decoding the Digital Gender Gap: Online Gender Bias is Stronger in Images than Text, Douglas Guilbeault and Solène Delecourt, Berkeley Haas School of Business
- April 19: CSS Forum: Moving Beyond the Model: Pretrial Risk Assessments in Practice, Alissa Skog, Senior Research Associate, California Policy Lab
- April 26: CSS Forum: A Relational View on Ethics and Technology, Bogdana Rakova, Data Scientist, Accenture Responsible AI
Previous Meetings
2021
- March 1: CSS Forum: Outercity Policing: Drivers of Police Spending in a Changing Metropolis, Ángel Ross, UC Berkeley Sociology
- Feb 22: CSS Forum: Loops, Ladders and Links: The Recursivity of Social and Machine Learning, Marion Fourcade, UC Berkeley Sociology; and Fleur Johns, UNSW Law
- Feb 8: CSS Forum: Serving Like an Organization: How Food-Service and Retail Workers Interpret Their Interactions With Customers, Adam Storer, UC Berkeley Sociology
- Feb 1: CSS Forum: Digital Health Equity and Access Lab, Adrian Aguilera and Caroline Figueroa, Berkeley School of Social Welfare
- Jan 21: TADA-BSSR Webinar: Avoiding the Pitfalls of Selection Bias, Carl T. Bergstrom, PhD, University of Washington
2020
- Nov 30: CSS Forum: Experiments on the Sociological Origins of Categories, Douglas Guilbeault, Assistant Professor, Management of Organizations, Haas School of Business, UC Berkeley
- Nov 16: CSS Forum: Constructing interval variables via faceted Rasch measurement and multitask deep learning: a hate speech application, Chris J. Kennedy (UC Berkeley and Harvard Medical School), Geoff Bacon (UC Berkeley), Alexander Sahn (UC Berkeley), and Claudia von Vacano (UC Berkeley)
- Nov 9: CSS Forum: Eviction, Displacement, Unemployment, and COVID-19 Infection Risk: Measuring Neighborhood Level Housing Precarity During the Pandemic, Tim Thomas, UC Berkeley Urban Displacement Project
- Nov 2: CSS Forum: The Accuracy, Equity, and Jurisprudence of Criminal Risk Assessme, Jennifer Skeem (UC Berkeley) and Christopher Slobogin (Vanderbilt Law School)
- Oct 26: CSS Forum: A university map of course knowledge, Zachary Pardos, Associate Professor, Graduate School of Education, UC Berkeley
- Oct 19: CSS Forum: Online education platforms scale college STEM instruction with equivalent learning outcomes at lower cost, Igor Chirikov, Center for Studies in Higher Education, Goldman School of Public Policy, UC Berkeley
- Oct 15: TADA-BSSR Webinar: Analyzing Complex Behavioral, Social and Population Health Data for COVID-19 & New Opportunities for Behavioral and Social Science Research (BSSR) Data Science Training, Elizabeth M. Ginexi, PhD, NIH Office of Behavioral and Social Sciences Research
- Oct 12: CSS Forum: Accelerating Computational Reproducibility in Economics (ACRE), Katie Hoeberling and Fernando Hoces de la Guardia, Berkeley Initiative for Transparency in the Social Sciences (BITSS)
- Oct 5: CSS Forum: Is being an only child harmful to psychological health?: Evidence from an instrumental variable analysis of China's One-Child Policy, Peng Ding, Statistics, UC Berkeley
- Sept 28: CSS Forum: A Supercomputer Reviews the Literature on Organizations: Combining Supervised and Unsupervised Text-Analysis Methods, Jaren Haber (Georgetown University), Heather A. Haveman (UC Berkeley), and Yoon Sung Hong (Wayfair)
- Sept 21: CSS Forum: The Emergence of Insight at the California Board of Parole Hearings, Isaac Dalke, UC Berkeley Sociology Department
- Sept 14: CSS Forum: How Do Threats Induce Information Seeking?: When Natural Experiments Meet Text Data, Jae Yeon Kim, UC Berkeley
