http://www.cse.iitd.ac.in/~ramanath/Site/About_me.html

AG 1, AG 2, AG 3, AG 4, AG 5, SWS, RG1, MMCI   Info

Public Audience

English

120 Minutes

Saarbrücken

Monitoring the formation and evolution of communities in large online social networks such as Twitter is an important problem that has generated considerable interest in both industry and academia. Fundamentally, the problem can be cast as studying evolving subgraphs (each subgraph corresponding to a topical community) on an underlying social graph – with users as nodes and the connection between them as edges. A key metric of interest in this setting is tracking the changes to the conductance of subgraphs induced by edge activations. This metric quantifies how well or poorly connected a subgraph is to the rest of the graph relative to its internal connections. Conductance has been demonstrated to be of great use in many applications, such as identifying bursty topics, tracking the spread of rumors, and so on. However, tracking this simple metric presents a considerable scalability challenge – the underlying social network is large, the number of communities that are active at any moment is large, the rate at which these communities evolve is high, and moreover, we need to track conductance in real-time.

Petra Schaaf

5000

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