Skip to Content

Computational Social Science (CSS) Initiative and Workshops

  1. All News
  2. All Events
    1. Seminar Series
    2. Annual Events
    3. Complexity and the Law
    4. Computational Social Science (CSS) Initiative and Workshops
    5. Archived Events

Vast streams of activity data from electronic sources make it possible to study human behavior with an unparalleled richness of detail. Social scientists can, for the first time, avail themselves of granular, disintermediated data to assemble individual narratives, motivations, and behavioral arcs as people go about living their lives. The aim of LSA's  Computational Social Science (CSS) Initiative is to develop a community where Michigan faculty and students can discuss topics of mutual interest, learn new skills, and create interdisciplinary collaborations. 

As part of this effort, we are organizing a series of methods workshops designed to provide introductions to important CSS-related models and techniques. Our fall lineup of workshops are described below.


Please note that, as part of each workshop, we will be serving a lunch on the 10th floor of Weiser Hall. We do hope you will take advantage of this opportunity to chat with fellow travelers in Computational Social Science.

  • 9:00 am - 4:30 pm
  • Room 747 Weiser Hall
  • There is no cost to attend

Each workshop will be limited to 30 participants and will be a full day event 9 am - 4:30 pm.  You must be able to participate all day to register. *In order to ensure that a broad array of disciplines are represented, registration will be limited during the first week to only 3-5 people from each Dept.  The week after registration opens, any unreserved spots will opened up to registrants from any department.  You will receive confirmation of registration after you register if there is space.




"Bayesian statistics for social scientists"

DR KEVIN QUINN University of Michigan - Department of Political Science

This workshop will introduce participants to some of the key ideas behind Bayesian inference while highlighting strengths and weaknesses of Bayesian approaches to some practical problems involving missing data, latent variables, and prediction. Computing will be a special focus and participants will spend time working through examples written in R.


"Communities, hierarchies, and cores: finding large-scale structure in complex networks"

DR DANIEL LARREMORE University of Colorado Boulder - Dept. of Computer Science & BioFrontiers Institute

This workshop will introduce the key concepts and techniques for finding and making sense of large-scale structure in complex networks. In addition to theory for community detection, hierarchy extraction, and core-periphery identification, we'll address a number of real-world applications, including social, genetic, and ecological networks. The workshop's methods will be applicable to any coding environment, with dedicated time to techniques in Python.


"Text as Data"

DR BRANDON STEWART Princeton University - Dept of Sociology

This workshop will cover the use of Text as Data in social science research. We will cover three key tasks that text analysis tools can help with: discovery, measurement and causal inference. The workshop will cover both some of the theory and methods for text analysis in the social sciences as well as hands-on experience applying these techniques in R.


Date Range


Select Tags (optional)