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Paper Abstract and Keywords
Presentation 2011-03-29 11:40
Topic Emergence Detection in Social Networks Using Probabilistic Models of Links
Toshimitsu Takahashi, Ryota Tomioka, Kenji Yamanishi (The Univ. of Tokyo) IBISML2010-128
Abstract (in Japanese) (See Japanese page) 
(in English) Detection of emerging topics from social network streams is becoming increasingly important these days. Conventional approaches based on textual information are not optimal for social networks because the contents exchanged over these networks are not only texts but more diverse. We focus on the links between users generated dynamically through mentions. We propose a probability model of users’ mentioning behavior and perform a change-point analysis over the anomaly scores based on the model. We experimentally confirm the effectiveness of the proposed probabilistic framework on three datasets we have collected from Twitter. The experimental results show that we can detect the emergence of topics at least as early as a word-based approach in the hindsight of the keyword best characterizing each topic.
Keyword (in Japanese) (See Japanese page) 
(in English) Topic detection / Change-point analysis / Sequentially discounting normalized maximum likelihood coding / / / / /  
Reference Info. IEICE Tech. Rep., vol. 110, no. 476, IBISML2010-128, pp. 169-176, March 2011.
Paper # IBISML2010-128 
Date of Issue 2011-03-21 (IBISML) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
Copyright
and
reproduction		 All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF IBISML2010-128

Conference Information
Committee IBISML  
Conference Date 2011-03-28 - 2011-03-29 
Place (in Japanese) (See Japanese page) 
Place (in English) Nakanoshima Center, Osaka Univ. 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Text and Web mining, etc. 
Paper Information
Registration To IBISML 
Conference Code 2011-03-IBISML 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Topic Emergence Detection in Social Networks Using Probabilistic Models of Links 
Sub Title (in English)  
Keyword(1) Topic detection  
Keyword(2) Change-point analysis  
Keyword(3) Sequentially discounting normalized maximum likelihood coding  
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1st Author's Name Toshimitsu Takahashi  
1st Author's Affiliation The University of Tokyo (The Univ. of Tokyo)
2nd Author's Name Ryota Tomioka  
2nd Author's Affiliation The University of Tokyo (The Univ. of Tokyo)
3rd Author's Name Kenji Yamanishi  
3rd Author's Affiliation The University of Tokyo (The Univ. of Tokyo)
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Speaker Author-1 
Date Time 2011-03-29 11:40:00 
Presentation Time 20 minutes 
Registration for IBISML 
Paper # IBISML2010-128 
Volume (vol) vol.110 
Number (no) no.476 
Page pp.169-176 
#Pages 8 
Date of Issue 2011-03-21 (IBISML) 

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