Computational Perspectives on Social Phenomena in On-Line Networks


December 7, 2011


With an increasing amount of social interaction taking place in the digital domain, and often in public on-line settings, we are accumulating enormous amounts of data about phenomena that were once essentially invisible to us: the collective behavior and social interactions of hundreds of millions of people, recorded at unprecedented levels of scale and resolution. Analyzing this data computationally offers new insights into the design of on-line applications, as well as a new perspective on fundamental questions in the social sciences. We discuss how this perspective can be applied to questions involving network structure and the dynamics of interaction among individuals, with a particular focus on the ways in which evaluation, opinion, and in some cases polarization manifest themselves at large scales in the on-line domain


Jon Kleinberg

Jon Kleinberg is the Tisch University Professor in the Computer Science Department at Cornell University. His research focuses on issues at the interface of networks and information, with an emphasis on the social and information networks that underpin the Web and other on-line media. He is a member of the National Academy of Sciences, the National Academy of Engineering, and the American Academy of Arts and Sciences, and serves on the Computer and Information Science and Engineering (CISE) Advisory Committee of the National Science Foundation, and the Computer Science and Telecommunications Board (CSTB) of the National Research Council. He is the recipient of MacArthur, Packard, and Sloan Foundation Fellowships, as well as awards including the Nevanlinna Prize from the International Mathematical Union and the ACM-Infosys Foundation Award in the Computing Sciences