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Title:SCENE: Structural Conversation Evolution Network
Author(s):Danilevsky, Marina
Advisor(s):Han, Jiawei
Department / Program:Computer Science
Discipline:Computer Science
Degree Granting Institution:University of Illinois at Urbana-Champaign
Subject(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.
Issue Date:2011-08-25
Rights Information:Copyright 2011 by Marina Grigoryevna Danilevsky. All rights reserved.
Date Available in IDEALS:2011-08-25
Date Deposited:2011-08

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