Networks with Positive and Negative Ties


February 25, 2010


Relations between users on social media sites often reflect a mixture of positive (friendly) and negative (antagonistic) interactions. We study how the interplay between positive and negative relationships affects the structure of on-line social networks, whereas in contrast the bulk of research on social networks to date has focused almost exclusively on positive interpretations of links between people. We connect our analyses to theories of signed networks from social psychology. In doing so we find that the classical theory of structural balance tends to capture certain common patterns of interaction, but that it is also at odds with some of the fundamental phenomena we observe — particularly related to the evolving, directed nature of these on-line networks. We then develop an alternate theory of status that better explains the observed edge signs and provides insights into the underlying social mechanisms. Our work provides one of the first large-scale evaluations of theories of signed networks using on-line datasets, as well as providing a perspective for reasoning about social media sites.

Joint work with Daniel Huttenlocher and Jon Kleinberg.


Jure Leskovec

Jure Leskovec is an Assistant Professor of Computer Science at Stanford University. His research focuses on mining and modeling large social and information networks, their evolution, and diffusion of information and influence over them. Problems he investigates are motivated by large scale data, the Web and on-line media. He received of three best paper awards and a ACM KDD dissertation award, won the ACM KDD Cup in 2003 and topped the Battle of the Sensor Networks 2007 competition. Jure also holds three patents and co-chairs the Machine Learning and Data Mining track at the upcoming World Wide Web conference.