ID | 116756 |
Author |
Matsumoto, Kazuyuki
Tokushima University
Tokushima University Educator and Researcher Directory
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Kishima, Ryota
Tokushima University
Tsuchiya, Seiji
Doshisha University
Hirobayashi, Tomoki
Yamada Denken
Yoshida, Minoru
Tokushima University
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Kita, Kenji
Tokushima University
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|
Keywords | Deep Neural Networks
Harmful Expression
Internet Flaming Detection
MBTI
Personality
Sentence Embeddings
Text Classification
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Content Type |
Journal Article
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Description | This paper hypothesizes that harmful utterances need to be judged in the context of whole sentences, and the authors extract features of harmful expressions using a general-purpose language model. Based on the extracted features, the authors propose a method to predict the presence or absence of harmful categories. In addition, the authors believe that it is possible to analyze users who incite others by combining this method with research on analyzing the personality of the speaker from statements on social networking sites. The results confirmed that the proposed method can judge the possibility of harmful comments with higher accuracy than simple dictionary-based models or models using a distributed representation of words. The relationship between personality patterns and harmful expressions was also confirmed by an analysis based on a harmful judgment model.
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ISBN | 9781799894001
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Journal Title |
International Journal of Information Technology and Web Engineering
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ISSN | 15541045
15541053
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NCID | AA12074076
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Publisher | IGI Global
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Volume | 17
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Issue | 1
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Start Page | 54
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Published Date | 2022
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Rights | This article published as an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and production in any medium, provided the author of the original work and original publication source are properly credited.
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DOI (Published Version) | |
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language |
eng
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TextVersion |
Publisher
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departments |
Science and Technology
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