Eric Gilbert

egilber2@cs.uiuc.edu

Title

Computing Tie Strength

Abstract

Relationships are the heart of social media: they make it *social*. Yet from a computational standpoint, we understand very little, if anything, about the relationships expressed there. Within Facebook, for instance, what makes two people close? Is it mostly a function of how long they'’ve been friends? How often they talk? What they say? Or the people they mutually know? Sociologists refer to the strength of a relationship as tie strength, the difference between a best friend and a distant colleague. I will present my work on modeling tie strength computationally, and how it can act as a tool in both design and analysis. Specifically, I'll present We Meddle (http://wemeddle.com), a Twitter application I built that puts tie strength at the heart of its design. We Meddle explores both the generalizability and design utility of computational tie strength. Finally, I'll present a research agenda comprising exciting problems facing social computing, such as how ultra-successful communities can guide new contributions by learning from old ones.

Bio

Gilbert is a PhD candidate in computer science at the University of Illinois. His research is in social computing, but might be better described as computer science inspired by sociology. Before coming to UIUC, he taught high school in Chicago as part of Teach For America. His research has examined tie strength, product reviewers, rural social media use, and argumentation in blog comments. Gilbert has received the best paper award three times from ACM SIGCHI, and he holds the Google Fellowship in Social Computing. Right now, he's thinking a lot about people who review products and how emotions at a massive scale might tell us something interesting about the world.