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Paper Abstract and Keywords
Presentation 2021-01-18 10:55
Stinging-Word Detection in Tweets for Reducing Defamation Damage
Keigo Itoh, Komei Arasawa, Shun Hattori (Muroran Inst. of Tech.) IN2020-42
Abstract (in Japanese) (See Japanese page) 
(in English) Posting slanderous defamation on the Internet has been regarded as a social problem, and now it seems that the social awareness of the problem has become even stronger. Twitter, which represents SNS, has a function to limit the accounts that can reply to a user's posts, and takes measures such as deleting the tweets and suspending the accounts that are reported as NG. However, such measures are not radical ones to reduce slanderous defamation and reduce its damage. To solve this problem, this paper proposes a method to automatically judge whether or not a posted tweet is defaming someone or someone's doing/something. The basic judgment of defamation is made by pattern-matching words in a posted tweet with "Stinging Words" (such as abuse words and negative words) listed by the authors. Furthermore, this paper aims to develop a system that classifies defamation tweets as precisely and exhaustively as possible, by calculating the negative degree of tweets using Positive/Negative (PN) judgment and also by recognizing the target of a word (especially, stinging word) in a tweet using dependency analysis.
Keyword (in Japanese) (See Japanese page) 
(in English) Defamation Judgment / Dependency Analysis / Positive/Negative Judgment / Tweets / SNS / / /  
Reference Info. IEICE Tech. Rep., vol. 120, no. 311, IN2020-42, pp. 7-12, Jan. 2021.
Paper # IN2020-42 
Date of Issue 2021-01-11 (IN) 
ISSN Online edition: ISSN 2432-6380
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)
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Conference Information
Committee IN  
Conference Date 2021-01-18 - 2021-01-19 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Contents Distribution, Social Networking Services, Data Analytics and Processing Platform, Big data, etc. 
Paper Information
Registration To IN 
Conference Code 2021-01-IN 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Stinging-Word Detection in Tweets for Reducing Defamation Damage 
Sub Title (in English)  
Keyword(1) Defamation Judgment  
Keyword(2) Dependency Analysis  
Keyword(3) Positive/Negative Judgment  
Keyword(4) Tweets  
Keyword(5) SNS  
1st Author's Name Keigo Itoh  
1st Author's Affiliation Muroran Institute of Technology (Muroran Inst. of Tech.)
2nd Author's Name Komei Arasawa  
2nd Author's Affiliation Muroran Institute of Technology (Muroran Inst. of Tech.)
3rd Author's Name Shun Hattori  
3rd Author's Affiliation Muroran Institute of Technology (Muroran Inst. of Tech.)
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Speaker Author-1 
Date Time 2021-01-18 10:55:00 
Presentation Time 25 minutes 
Registration for IN 
Paper # IN2020-42 
Volume (vol) vol.120 
Number (no) no.311 
Page pp.7-12 
Date of Issue 2021-01-11 (IN) 

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