Gossip: Identifying Central Nodes in a Social Network

NICO Annual Distinguished Speaker Series, Thursday, May 29, 2014, 3:00PM Jacobs Center G40, 4-5:30PM Reception 6th Floor

A presentation and reception brought to you by the Northwestern Institute on Complex Systems (NICO) in partnership with the Kellogg School of Management’s Center for Mathematical Studies in Economics and Management Science (CMS-EMS) and the Kellogg Architectures of Collaboration Initiative (KACI).

Professor Matthew Jackson, Stanford University

Abstract
How can we identify the most influential nodes in a network for initiating diffusion? Are people able to easily identify those people in their communities who are best at spreading information, and if so How?  Using theory and recent data, we will examine these questions and see how the structure of social networks affects information transmission ranging from gossip to the diffusion of new products.  In particular, a model of diffusion is used to define centrality and shown to nest degree centrality, eigenvector centrality, and other measures of centrality as extreme special cases.  Then it will be shown that by tracking gossip within a network, nodes can easily learn to rank the centrality of other nodes without knowing anything about the network itself.  The theoretical predictions are consistent with data from rural India.  

Past NICO Annual Distinguished Speakers:
Mark Newman
Steven Strogatz
Alex Vespignani