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Paper Abstract and Keywords
Presentation 2020-02-16 14:45
Trend analysis of media company SNS account based on user reaction time
Takeshi Sakaki (HTL), Fujio Toriumi (UT) NLC2019-37
Abstract (in Japanese) (See Japanese page) 
(in English) In recent years, due to the spread of web and SNS, various problems related to information diffusion such as the spread of fake news and the occurrence of echo chambers have become apparent. Under these circumstances, techniques to evaluate the reliability and bias of information and information sources
have been being developed. In this study, we focus on the incitement as one of information source features (hereinafter, media), and propose a quantitative index to evaluate it. We define {it user reaction time}, which is How fast the user spreads the information which he/she received, as a clue to estimate the degree of incitement. We proposed an index that summed up user reaction time for each media as an index indicating the incitement. As a result, it was suggested that the proposed index tended to have a unique value depending on the media, irrespective of the article and the degree of article diffusion. In the future, we will conduct large-scale user evaluation experiments to further verify the validity of the proposed index.
Keyword (in Japanese) (See Japanese page) 
(in English) information diffusion / social media analysis / web mining / / / / /  
Reference Info. IEICE Tech. Rep., vol. 119, no. 415, NLC2019-37, pp. 7-11, Feb. 2020.
Paper # NLC2019-37 
Date of Issue 2020-02-09 (NLC) 
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 NLC  
Conference Date 2020-02-16 - 2020-02-17 
Place (in Japanese) (See Japanese page) 
Place (in English) Seikei University 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Integration of verbal and non-verbal information 
Paper Information
Registration To NLC 
Conference Code 2020-02-NLC 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Trend analysis of media company SNS account based on user reaction time 
Sub Title (in English)  
Keyword(1) information diffusion  
Keyword(2) social media analysis  
Keyword(3) web mining  
1st Author's Name Takeshi Sakaki  
1st Author's Affiliation Hottolink, Inc. (HTL)
2nd Author's Name Fujio Toriumi  
2nd Author's Affiliation the University of Tokyo (UT)
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Speaker Author-1 
Date Time 2020-02-16 14:45:00 
Presentation Time 25 minutes 
Registration for NLC 
Paper # NLC2019-37 
Volume (vol) vol.119 
Number (no) no.415 
Page pp.7-11 
Date of Issue 2020-02-09 (NLC) 

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