Relationship Between Personality Patterns and Harmfulness: Analysis and Prediction Based on Sentence Embedding

INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY AND WEB ENGINEERING(2022)

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摘要
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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关键词
Deep Neural Networks, Harmful Expression, Internet Flaming Detection, MBTI, Personality, Sentence Embeddings, Text Classification
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