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- Kazuyuki Matsumoto
- Tokushima University, Japan
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- Ryota Kishima
- Tokushima University, Japan
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- Seiji Tsuchiya
- Doshisha University, Japan
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- Tomoki Hirobayashi
- Yamada Denken Co., Ltd., Japan
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- Minoru Yoshida
- Tokushima University, Japan
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- Kenji Kita
- Tokushima University, Japan
書誌事項
- タイトル別名
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- Analysis and Prediction Based on Sentence Embedding
説明
<p>This paper hypothesize that harmful utterances need to be judged in context of whole sentences, and extract features of harmful expressions using a general-purpose language model. Based on the extracted features, we 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 representations of words. The relationship between personality patterns and harmful expressions was also confirmed by an analysis based on a harmful judgment model.</p>
収録刊行物
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- International Journal of Information Technology and Web Engineering
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International Journal of Information Technology and Web Engineering 17 (1), 1-24, 2022-02-23
IGI Global
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キーワード
詳細情報 詳細情報について
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- CRID
- 1360298336571568640
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- ISSN
- 15541053
- 15541045
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- データソース種別
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- Crossref
- KAKEN
- OpenAIRE