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Friday, November 1, 2013 at 3:30pm
A growing set of online applications are generating data that can be viewed as very large collections of small, dense social graphs — these range from sets of social groups, events, or collaboration projects to the vast collection of graph neighborhoods in large social networks. A natural question is how to usefully define a domain-independent `coordinate system’ for such a collection of graphs, so that the set of possible structures can be compactly represented and understood within a common space.
We discuss some of the issues that come into play when we try to analyze this type of network data, focusing both on the underlying combinatorial problems and also on questions that flow more directly from the applications of these methods. In particular, given a snapshot of an individual’s network neighborhood, how do we recognize his or her most significant social ties? We describe some of the consequences of a graph-theoretic measure of “dispersion” that turns out to be remarkably effective in practice at identifying a person’s spouse or romantic partner.
The talk is based on joint work with Lars Backstrom and Johan Ugander.
Cornell Engineering, Computer Science, Center for Applied Mathematics, Cornell Bowers Computing and Information Science
Jon Kleinberg
Department of Computer Science, Cornell University
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