Social Information Foraging and Sensemaking

Tuesday, November 16, 2010 - 9:23am


Wednesday, November 17, 2010
2:00 PM – 3:00 PM
Computer Science Conference Room, Harold Frank Hall Rm. 1132

HOST: Tobias Hollerer

SPEAKER: Peter Pirolli
Palo Alto Research Center

Title: Social Information Foraging and Sensemaking


Information Foraging Theory is a theory of human-information interaction that aims to explain and predict how people will best shape themselves to their information environments, and how information environments can best be shaped to people. The approach involves a kind of reverse engineering in which the theorist asks (a) what is the nature of the task and information environments, (b) why is a given system a good solution to the problem, and (c) how is that “ideal” solution realized (approximated) by mechanism. Typically, the key steps in developing a model of information foraging involve: (a) a rational analysis of the task and information environment (often drawing on optimal foraging theory from biology) and (b) a computational production system model of the cognitive structure of task. I will briefly review work on individual information seeking, and then focus on how this work is being expanded to studies of information production and sensemaking in technology-mediated social systems such as wikis, social tagging, social network sites, and twitter. I will also discuss recent work on integrating information network and social network analysis to identify credible sources of information in twitter.


Peter Pirolli is a Research Fellow in the Augmented Social Cognition Area at the Palo Alto Research Center (PARC), where he has been pursuing studies of human information interaction since 1991. Prior to joining PARC, he was an Associate Professor in the School of Education at UC Berkeley. Pirolli received his doctorate in cognitive psychology from Carnegie Mellon University in 1985. He is an elected Fellow of the American Association for the Advancement of Science, the Association for Psychological Science, the National Academy of Education, and the ACM Computer-Human Interaction Academy.