Building on the success of our inaugural event in 2023, the Center for Applied Social and Economic Research (CASER) at NYU Shanghai, jointly with the School of Social Development, East China Normal University are proud to continue fostering innovation and collaboration in computational social science with the 2025 Summer Institute in Computational Social Science (SICSS). From June 24 to June 30, 2025, this year’s SICSS-NYU Shanghai will once again bring together graduate students, postdoctoral researchers, and early-career faculty to explore cutting-edge methods and applications in the field. SICSS is for both social scientists (broadly conceived) and data scientists (broadly conceived).

The instructional program will involve lectures, group problem sets, and participant-led research projects. There will also be outside speakers who conduct computational social science research in a variety of settings, such as academia, industry, and government. Topics covered include text as data, website scraping, digital field experiments, machine learning, and ethics. There will be ample opportunities for students to discuss their ideas and research with the organizers, other participants, and visiting speakers. Because we are committed to open and reproducible research, all materials created by faculty and students for the Summer Institute will be released open source.

 

Participation is restricted to graduate students, postdoctoral researchers, and early career faculty. We welcome applicants from all backgrounds and fields of study, especially applicants from groups currently under-represented in computational social science. About 25 participants will be invited, and participants are expected to fully attend and participate in the entire one-week program. This event is free of charge. The participants are expected to cover their own travel and accommodation expenses during this event. But CASER will provide scholarships for up to 10 participants to subsidize their lodging expenses. All participants will receive some meal allowances.