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CIKM
2006
Springer

Topic evolution and social interactions: how authors effect research

9 years 3 months ago
Topic evolution and social interactions: how authors effect research
We propose a method for discovering the dependency relationships between the topics of documents shared in social networks using the latent social interactions, attempting to answer the question: given a seemingly new topic, from where does this topic evolve?. In particular, we seek to discover the pair-wise probabilistic dependency in topics of documents which associate social actors from a latent social network, where these documents are being shared. By viewing the evolution of topics as a Markov chain, we estimate a Markov transition matrix of topics by leveraging social interactions and topic semantics. Metastable states in a Markov chain are applied to the clustering of topics. Applied to the CiteSeer dataset, a collection of documents in academia, we show the trends of research topics, how research topics are related and which are stable. We also show how certain social actors, authors, impact these topics and propose new ways for evaluating author impact. Categories and Subjec...
Ding Zhou, Xiang Ji, Hongyuan Zha, C. Lee Giles
Added 20 Aug 2010
Updated 20 Aug 2010
Type Conference
Year 2006
Where CIKM
Authors Ding Zhou, Xiang Ji, Hongyuan Zha, C. Lee Giles
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