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 |
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) |
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NLC2019-37 |
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) |
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information diffusion |
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social media analysis |
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web mining |
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1st Author's Name |
Takeshi Sakaki |
1st Author's Affiliation |
Hottolink, Inc. (HTL) |
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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 |
#Pages |
5 |
Date of Issue |
2020-02-09 (NLC) |
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