Computational Social Science for Business

Uniting computer science, statistics, and social science to solve real-life problems through mass collaboration on path-breaking transparent research in partnership with industry, government, and civil society.


Designing and running innovative, large-scale experiments to pursue replicable, generalizable, scalable, and ultimately useful social science. 

Building technology to detect patterns of bias and misinformation in media from across the political spectrum and spanning television, radio, social media, and the broader web.

Using cutting-edge statistical techniques to analyze police-civilian interactions, measure racial bias in policing, evaluate policing policy reforms, and improve the performance of policing agencies.

Using mobility and demographic data to train epidemiological models designed to predict the impact of policies around reopening and vaccination.


The Computational Social Science Lab was created in March 2021 as a joint venture of the School of Engineering and Applied Science, the Annenberg School for Communication, and the Wharton School. We seek novel, replicable insights into societally relevant problems by applying computational methods to large-scale data. Through our research infrastructure, industry partnerships, and network of collaborators, we also aim to facilitate progress in computational social science more generally.

In the News

Don’t be too quick to blame social media for America’s polarization

Studies of online echo chambers don’t paint the full picture of Americans’ political segregation. New research shows that the problem is more Fox News and MSNBC than Facebook and Twitter.

Want to reduce political polarization?

Start by looking beyond politics. New research from PIK University Professor Duncan Watts sheds light on how even hardliners can be swayed when coming in contact with opposing viewpoints.

The Data Will Save Us

Or at least, that’s the hope of Wharton professor Duncan Watts, whose new initiative, the Penn Media Accountability Project, aims to expose bias in journalism by building a huge database of news for researchers and journalism watchdogs to analyze.

The Team

Computational Social Science for Business encompasses two collaborative research teams with shared interests and interrelated research agendas, lead by Professors Duncan Watts and Dean Knox.


Professor Duncan Watts - Analytics at Wharton Faculty Fellow

Duncan Watts
Stevens University Professor & twenty-third Penn Integrates Knowledge Professor

Professor Dean Knox - Analytics at Wharton Faculty Fellow

Dean Knox
Assistant Professor
Operations, Information and Decisions

Administrative Staff

Jeanne Ruane
Executive Director

Rachel Mariman
Senior Research Project Manager

Emma Arsekin
Communications Specialist

Haosen Ge
Data Scientist

Tuti Gomoka
Senior Research Coordinator

Miguel Rivera-Lanas
Data Scientist

Eric Shapiro
Research Operations Manager

Research Staff

Homa Hosseinmardi
Associate Research Scientist

James Houghton
Postdoctoral Researcher

Mark Whiting
Senior Computational Social Scientist