The Social Side of Recommendation Systems: How Groups Shape Our Decisions
Recommendation systems occupy an expanding role in everyday decision
making, from choice of movies and household goods to consequential
medical and legal decisions. This talk will explore a sequence of
work related to recommending decisions for people to take. First we
will examine the results of a large-scale study of television viewing
habits, focusing on how individuals adapt their preferences when
consuming content with others. Next, we will leverage our insights
about the social behavior of individuals to incorporate social network
information into a model for providing personalized recommendations.
Finally, we will consider the impacts of recommendation algorithms
like these on human choices and the homogeneity of group behavior.
Allison Chaney is an IC Postdoctoral Research Fellow at Princeton University, currently working with with Barbara Engelhardt and Brandon Stewart. She also received her Ph.D. in Computer Science at Princeton, under the advisement of David Blei, and holds a B.A. in Computer Science and a B.S. in Engineering from Swarthmore College. Her research focuses on developing scalable and interpretable machine learning methods to identify influences on human behavior.