Workshops & Datathon

IC2S2 features two special events prior to the main conference: a datathon and a series of skills workshops.

Workshops are intended to be an introduction to core computing skills used in computational social science. It is a great opportunity for sociological researchers who are newcomers to computational techniques or who want to broaden their tool-kits with exposure to new methodologies.

To apply to attend workshops, review suggested preparation for the workshops and view a list of topics, visit the Workshops and Datathons page.


The datathon is a marathon research session in which participants work together to turn datasets into insight. Participants will utilize prepared datasets and computational methods to respond to a theory-driven prompt developed by a panel of judges.



Thematic panels will address issues such as social contagion, social dynamics and influence, political collective action, economical models, social media and more. Panels will be run concurrently and will feature nearly 150 speakers. Presenters will be from a diverse selection of research institutions and organizations. They will be from numerous countries and disciplines, and their commonality will be the contributions they are making to the field of computational social science.

IC2S2 brings together interdisciniplinary researchers to explore the biggest questions facing the field of computational social science.

About Computational Social Science

What is computational social science?
The application of computer science and big data techniques to social science research.

Why is computational social science emerging now?
Due to advances in machine learning and computational techniques, and the proliferation of digital footprints, human and societal behavior that was previously unquantifiable and unobservable now generates data that can be collected and analyzed to make insights and predictions.

Why is industry interested computational social science?

This ability to collect and analyze massive amounts of social and behavioral data is poised to disrupt and transform business intelligence, operations, and organization.

Sample of Computational Science Papers

“Big Data. Big Obstacles.”
Conley, Dalton et al.,
The Chronicle of Higher Education

“Computational Social Science: Exciting Progress and Future Directions”
Watts, Duncan J.,
National Academy of Engineering

“Computational Social Science”
Lazer, David, et al.,

"Is Bigger Always Better?"
Hargittai, Eszter,
The ANNALS of the American Academy of Political and Social Science

"The Ultimate Data Set - Computational Social Science Aims to Discover Universal Facts."
Uzzi, Brian,
Kellogg Insight

“Computational CAM: studying children and media in the age of big data”
Welles, Brooke Foucault,
Journal of Children and Media

“Computational Social Science”

Mann, Adam

June 24 – 26, 2016 /
General Session

22 – 23 June 2016 /

Kellogg School of Management at Northwestern University