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Semantic Social Network Analysis with Text Corpora

  • Dong-mei Yang
  • Hui Zheng
  • Ji-kun Yan
  • Ye Jin
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7301)

Abstract

We present the Document-Entity-Topic (DET) model for semantic social network analysis which tries to find out the interested entities through the topics we aim at, detect groups according to the entities which concern the similar topics, and rank the plentiful entities in a document to figure out the most valuable ones. DET model learns the topic distributions by the literal descriptions of entities. The model is similar to Author-Topic (AT) model, adding the key attribute that the distribution of entities in a document is not uniform but Dirichlet allocation. We experiment on the “Libya Event” data set which is collected from the Internet. DET model increases the precision on tasks of social network analysis and gives much lower perplexity than AT model.

Keywords

Semantic Social Network Analysis Topic Model Entity Modeling 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Dong-mei Yang
    • 1
  • Hui Zheng
    • 1
  • Ji-kun Yan
    • 2
  • Ye Jin
    • 2
  1. 1.Science and Technology on Blind Signal Processing LaboratoryChina
  2. 2.Southwest Electronics and Telecommunication Technology Research InstituteChina

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