SCENE: Structural Conversation Evolution Network

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.

Name thesis:degree_name

M.S.

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Computer Science

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2011

Author dc:creator

• Danilevsky, Marina

Contributors dc:contributor

• Han, Jiawei

• conversation network
• conversation evolution network
• conversation structure network

Statement dc:rights

• Copyright 2011 by Marina Grigoryevna Danilevsky. All rights reserved.

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/26234

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/26234