Director of Research (if dissertation) or Advisor (if thesis)
Han, Jiawei
Department of Study
Computer Science
Discipline
Computer Science
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Keyword(s)
conversation network
conversation evolution network
conversation structure network
Abstract
It’s not just what you say, but it is how you say it. To date, the majority of the Instant Message (IM) analysis and research has focused on the content of the conversation.The main research question has been, ‘what do people talk about?’ focusing on topic extraction and topic modeling. While content is clearly critical for many real-world applications, we have largely ignored identifying ‘how’ people communicate. Conversation structure and communication patterns provide deep insight into how conversations evolve, and how the content is shared. Motivated by theoretical work from psychology and linguistics in the area of conversation alignment, we introduce SCENE, an evolution network approach to extract knowledge from a conversation network. We demonstrate the potential of our approach by taking the task of matching conversation partners. We find that SCENE is more successful because, in contrast to existing approaches, SCENE treats a conversation as an evolving, rather than a static document, and focuses on the structural elements of the conversation instead of being tied to the specific content.
Graduation Semester
2011-08
Permalink
http://hdl.handle.net/2142/26234
Copyright and License Information
Copyright 2011 by Marina Grigoryevna Danilevsky. All rights reserved.
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