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Paper Abstract and Keywords
Presentation 2012-12-13 10:50
Classifying Twitter Users for Spatio-temporal Entity Retrieval
Liang Yan, Qiang Ma, Masatoshi Yoshikawa (Kyoto Univ.) DE2012-30
Abstract (in Japanese) (See Japanese page) 
(in English) Spatio-temporal entity retrieval is a task for searching the entities with certain time and certain place, such as some commodities or events, from Twitter and Facebook, the social network with mass real-time update information. On Twitter, there are some users who tweet to the unspecified large number of other users, such as shops or local governments etc, while some other users who almost tweets to their friends. In this paper, we call the former as open account, while the latter as closed account. The expression in tweets and credibility of the two type of users can be different. For example, sometimes, an open account said "there are still some stock in the shop" about a commodity, while a closed account said "I didn't get it". In order to improve the accuracy of spatio-temporal ER, it is necessary to classify Twitter users. In this paper, we propose the method to classify Twitter users into open accounts and closed accounts. We use both the feature of user profile, such as address or telephone number etc. and the followers distribution. If the followers distribution is scattered, we treat it open account, while closed account otherwise.
Keyword (in Japanese) (See Japanese page) 
(in English) Open account / Closed account / Followers Network / / / / /  
Reference Info. IEICE Tech. Rep., vol. 112, no. 346, DE2012-30, pp. 93-98, Dec. 2012.
Paper # DE2012-30 
Date of Issue 2012-12-05 (DE) 
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 DE2012-30

Conference Information
Committee DE  
Conference Date 2012-12-12 - 2012-12-13 
Place (in Japanese) (See Japanese page) 
Place (in English) Campus Plaza Kyoto 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Big Data & Social Computing, etc. 
Paper Information
Registration To DE 
Conference Code 2012-12-DE 
Language English 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Classifying Twitter Users for Spatio-temporal Entity Retrieval 
Sub Title (in English)  
Keyword(1) Open account  
Keyword(2) Closed account  
Keyword(3) Followers Network  
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1st Author's Name Liang Yan  
1st Author's Affiliation Kyoto University (Kyoto Univ.)
2nd Author's Name Qiang Ma  
2nd Author's Affiliation Kyoto University (Kyoto Univ.)
3rd Author's Name Masatoshi Yoshikawa  
3rd Author's Affiliation Kyoto University (Kyoto Univ.)
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Speaker Author-1 
Date Time 2012-12-13 10:50:00 
Presentation Time 25 minutes 
Registration for DE 
Paper # DE2012-30 
Volume (vol) vol.112 
Number (no) no.346 
Page pp.93-98 
#Pages 6 
Date of Issue 2012-12-05 (DE) 

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