June 16 to June 29, 2019 | Princeton University

Sponsored by the Russell Sage Foundation & The Alfred P. Sloan Foundation


From the evening of Sunday, June 16 to the morning of Saturday, June 29, 2019, the Russell Sage Foundation and the Alfred P. Sloan Foundation will sponsor the Summer Institute in Computational Social Science, to be held at Princeton University. The purpose of the Summer Institute is to bring together graduate students, postdoctoral researchers, and beginning faculty interested in computational social science. The Summer Institute is for both social scientists (broadly conceived) and data scientists (broadly conceived). The co-organizers and principal faculty of the Summer Institute are Christopher Bail and Matthew Salganik. In addition to the event at Princeton, there will also be a number of partner locations run by alumni of the 2017 and 2018 Summer Institute, which will be hosted at other universities.

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 academia, industry, and government. Topics covered include text as data, website scraping, digital field experiments, non-probability sampling, mass collaboration, 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 Ph.D. students, postdoctoral researchers, and untenured faculty within 7 years of their Ph.D. Most participant costs during the workshop, including housing and most meals, will be covered, and most travel expenses will be reimbursed up to a set cap. We welcome applicants from all backgrounds and fields of study, especially applicants from groups currently under-represented in computational social science. About thirty participants will be invited.

Application materials are due Tuesday, February 20, 2019.

Faculty

Matthew Salganik

Matthew Salganik is Professor of Sociology at Princeton University, and he is affiliated with several of Princeton’s interdisciplinary research centers: the Office for Population Research, the Center for Information Technology Policy, the Center for Health and Wellbeing, and the Center for Statistics and Machine Learning. His research interests include social networks and computational social science. He is the author of the forthcoming book Bit by Bit: Social Research in the Digital Age.

Chris Bail

Chris Bail is the Douglas and Ellen Lowey Associate Professor of Sociology and Public Policy at Duke University and a member of the Interdisciplinary Program on Data Science, the Duke Network Analysis Center, and the Duke Population Research Institute. His research examines how non-profit organiations and other political actors shape social media discourse using large text-based datasets and apps for social science research. He is the author of Terrified: How Anti-Muslim Fringe Organizations Became Mainstream.

Pre-arrival

As we discussed in our call for applications, we have arranged two types of training prior to the event this summer. Some students have more sophisticated coding skills but little exposure to social science; other students have significant exposure to social science but lack coding skills.

Coding

The majority of the coding work presented at the 2019 SICSS will employ R. However, you are welcome to employ a language of your choice, such as Python, Julia, or other languages that are commonly used by computational social scientists. If you would like to work in R, we recommend that you complete the following courses within DataCamp, a website with courses on many topics related to data science. Obviously, you only need to complete the classes with material that you would like to learn.

We thank DataCamp for making these materials avaialble to admitted participants though their DataCamp for the Classroom program.

If you would like a different way to learn similar material, we recommend Introduction to R for Social Scientists taught by Charles Lanfear. This course includes video, code, and assignments.

Reading List

The Summer Institute will bring together people from many fields, and therefore we think that asking you to do some reading before you arrive will help us use our time together more effectively. First, we ask you to read Matt’s book, Bit by Bit: Social Research in the Digital Age, which is a broad introduction to computational social science. Parts of this book will be review for most of you, but if we all read this book ahead of time, then we can use our time together for more advanced topics.

Also, for students with little or no exposure to sociology, economics, or political science, we have assembled a collection of exemplary papers in the core areas addressed by the Russell Sage Foundation. Neither your work nor the work we develop together at the institute need map neatly onto these categories, but if those with less exposure to social science read these, we will increase the chances of interdisciplinary cross-pollination, which we view as critical to the future of computational social science.

Future of Work

Behavioral Economics

Race, Ethnicity, and Immigration

Social Inequality