The Computational Social Science Workshop Presents
James Evans
Director, Knowledge Lab; Professor, Sociology, University of Chicago; Senior Fellow, Computation Institute; Faculty Director, Masters Program in Computational Social Sciences
**Abstract:** As political polarization in the United States continues to rise, the question of whether polar- ized individuals can fruitfully cooperate becomes pressing. Although diversity of individual perspectives typically leads to superior team performance on complex tasks, strong political perspectives have been associated with conflict, misinformation and a reluctance to engage with people and perspectives beyond one’s echo chamber. It is unclear whether self-selected teams of politically diverse individuals will create higher or lower quality outcomes. In this paper, we explore the effect of team political composition on performance through analysis of millions of edits to Wikipedia’s Political, Social Issues, and Science articles. We measure editors’ political alignments by their contributions to conservative versus liberal articles. A survey of editors validates that those who primarily edit liberal articles identify more strongly with the Democratic party and those who edit conservative ones with the Republican party. Our analysis then reveals that polarized teams—those consisting of a balanced set of polit- ically diverse editors—create articles of higher quality than politically homogeneous teams. The effect appears most strongly in Wikipedia’s Political articles, but is also observed in So- cial Issues and even Science articles. Analysis of article “talk pages” reveals that politically polarized teams engage in longer, more constructive, competitive, and substantively focused but linguistically diverse debates than political moderates. More intense use of Wikipedia policies by politically diverse teams suggests institutional design principles to help unleash the power of politically polarized teams.
Thursday, 1/25/2018
11:00am-12:20pm
Kent 120
A light lunch will be provided by Good Earth Catering Company.
**Dr. Evans** focuses on the collective system of thinking and knowing, ranging from the distribution of attention and intuition, the origin of ideas and shared habits of reasoning to processes of agreement (and dispute), accumulation of certainty (and doubt), and the texture—novelty, ambiguity, topology—of human understanding. He is especially interested in innovation—how new ideas and practices emerge—and the role that social and technical institutions (e.g. the Internet, markets, collaborations) play in collective cognition and discovery. Much of his work has focused on areas of modern science and technology, but he is also interested in other domains of knowledge—news, law, religion, gossip, hunches and historical modes of thinking and knowing. He supports the creation of novel observatories for human understanding and action through crowd sourcing, information extraction from text and images, and the use of distributed sensors (e.g. RFID tags, cell phones). He uses machine learning, generative modeling, social and semantic network representations to explore knowledge processes, scale up interpretive and field-methods, and create alternatives to current discovery regimes. His research is funded by the National Science Foundation, the National Institutes of Health, the Templeton Foundation and other sources, and has been published in Science, American Journal of Sociology, Social Studies of Science,Administrative Science Quarterly, PLoS Computational Biology and other journals. His work has been featured in Nature, the Economist, Atlantic Monthly, Wired, NPR, BBC, El País, CNN and many other outlets.
At Chicago, Dr. Evans is the Director of Knowledge Lab (http://knowledgelab.org), which has collaborative, granting and employment opportunities, as well as ongoing seminars. He also sponsors the Computational Social Science workshop (with John Brehm) and the Knowledge-Value workshop (with John Kelly) and co-organizes the Rational Choice workshop (with Gary Becker, Richard Posner & Glen Weyl). He teaches courses in the history of modern science, science studies, computational content analysis, and Internet and Society. Before Chicago, he received his doctorate in sociology from Stanford University, served as a research associate in the Negotiation, Organizations, and Markets group at Harvard Business School, started a private high school focused on project-based arts education, and completed a BA in Anthropology and Economics at Brigham Young University.
The 2017-2018 Computational Social Science Workshop meets each Thursday from 11 a.m. to 12:20 p.m. in Kent 120. All interested faculty and graduate students are welcome.
Students in the Masters of Computational Social Science program are expected to attend and join the discussion by posting a comment on the issues page of the workshop's public repository on GitHub. Further instructions are documented in the Computational Social Science Workshop's README on Github.