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. In addition to research internships at Microsoft Research and Hunch/eBay, she has previously worked for Pixar Animation Studios and the Yorba Foundation. Her research focuses on developing scalable and interpretable machine learning methods to identify influences on human behavior.