Can meaningful relationships be inferred from online social network connections? - Ben Zhao Thursday, April 9

Event Date: 

Thursday, April 9, 2009 - 12:00pm

Ben Zhao

Social networks are popular platforms for interaction, communication and collaboration between friends. Researchers have recently proposed an emerging class of applications that leverage relationships from social networks to improve security and performance in applications such as email, web browsing and overlay routing. While these applications often cite social network connectivity statistics to support their designs, researchers in psychology and sociology have repeatedly cast doubt on the practice of inferring meaningful relationships from social network connections alone. This leads to the question: Are social links valid indicators of real user interaction? If not, then how can we quantify these factors to form a more accurate model for evaluating socially-enhanced applications? In this talk, we address this question through a detailed study of user interactions in the Facebook social network. We propose the use of interaction graphs to impart meaning to online social links by quantifying user interactions. We analyze interaction graphs derived from Facebook user traces and show that they exhibit significantly lower levels of the ``small-world'' properties shown in their social graph counterparts. This means that these graphs have fewer ``supernodes'' with extremely high degree, and overall network diameter increases significantly as a result. To quantify the impact of our observations, we use both types of graphs to validate two well-known social-based applications (RE and SybilGuard). The results reveal new insights into both systems, and confirm our hypothesis that studies of social applications should use real indicators of user interactions in lieu of social graphs.

Ben is a faculty member at the Computer Science department, U.C. Santa Barbara. Before UCSB, he completed his M.S. and Ph.D. degrees in Computer Science at U.C. Berkeley. His research spans the areas of networking, security and privacy, distributed systems, simulation and modeling. He received his B.S. degree from Yale University (BR'97). He is a recent recipient of the National Science Foundation's CAREER award, MIT Tech Review's TR-35 Award (Young Innovators Under 35), and ComputerWorld's Top 40 Technology Innovators.