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Characterizing Diverse Link Patterns in Complex Networks

Yanhua Li, Ph.D. Candidate in Computer Science, University of Minnesota, Twin Cities, USA
12 April 2013 - 11:00am

Sala de Juntas 3.3.B01 - Building Rey Pastor (Biblioteca), University Carlos III of Madrid, Avda. Universidad, 30, 28911 Leganés – Madrid


Complex networks, including the Internet, wireless and cellular networks, and on-line social networks, are becoming indispensable parts of our daily lives. These networks arising from a wide range of applications can be represented and studied as graphs, and the underlying link patterns play an important role in understanding and solving problems in such applications. For example, many online social networks, such as Twitter and Google+, can be viewed as directed graphs with uni-directional "following'' relations among users, and the link directions contain crucial information about how users form social communities. In another application, online social networks such as Slashdot and Epinions represent relationships between users as links with positive or negative weights, which correspond to friend and foe relations. These networks are referred to as signed networks, where those signed links generate new challenges in understanding and studying the underlying network properties. In this talk, I present my work on developing theories for studying and characterizing various crucial graph properties, such as the edge directionality in directed graphs and the edge polarity in signed graphs. I do so by emphasizing on applications to detecting stable social communities and understanding social influence propagation patterns on online social networks.

About Yanhua Li:

Yanhua Li is a Ph.D. candidate in Computer Science at the University of Minnesota, Twin Cities. He obtained his first Ph.D. in Electrical Engineering from Beijing University of Posts and Telecommunications in 2009. His broad research interests are in analyzing, understanding, and making sense of big data generated from various complex networks in many contexts. His specific interests include online social behavior modeling and analysis, high performance networking protocol design, spectral graph theory, and large-scale network sampling, measurement, and mining. He has interned in Bell Labs in New Jersey, Microsoft Research Asia, and HUAWEI research labs of America. His work has been published by top conferences and journals in both networking and data mining areas, such as INFOCOM, ICDCS, WSDM, IMC, IEEE/ACM ToN, IEEE TVT, Internet Mathematics, etc. He has one filed US patent.

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This event will be conducted in English

Image: By Stomchak (Own work) [Public domain], via Wikimedia Commons


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