Kazuyuki Matsumoto, Ryota Kishima, S. Tsuchiya, Tomoki Hirobayashi, Minoru Yoshida, K. Kita
{"title":"人格模式与危害性的关系:基于句子嵌入的分析与预测","authors":"Kazuyuki Matsumoto, Ryota Kishima, S. Tsuchiya, Tomoki Hirobayashi, Minoru Yoshida, K. Kita","doi":"10.4018/ijitwe.298654","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":222340,"journal":{"name":"Int. J. Inf. Technol. Web Eng.","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Relationship Between Personality Patterns and Harmfulness: Analysis and Prediction Based on Sentence Embedding\",\"authors\":\"Kazuyuki Matsumoto, Ryota Kishima, S. Tsuchiya, Tomoki Hirobayashi, Minoru Yoshida, K. Kita\",\"doi\":\"10.4018/ijitwe.298654\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":222340,\"journal\":{\"name\":\"Int. J. Inf. Technol. Web Eng.\",\"volume\":\"2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Int. J. Inf. Technol. Web Eng.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4018/ijitwe.298654\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Inf. Technol. Web Eng.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/ijitwe.298654","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Relationship Between Personality Patterns and Harmfulness: Analysis and Prediction Based on Sentence Embedding
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.