{"title":"运用提示学习识别社交媒体中的冒犯性语言。","authors":"Leilei Su, Yifan Peng, Zezheng Wang, Cong Sun","doi":"10.1109/ichi57859.2023.00122","DOIUrl":null,"url":null,"abstract":"<p><p>Offensive language refers to the use of language in a manner that may offend or harm others who are within earshot or view in a public place. Given the importance of identifying such language in social media for promoting emotional well-being, we propose a prompt learning method and compare its performance with fine-tuning on two widely used datasets, HatEval and OffensEval. Experimental results demonstrate that prompt learning can achieve a performance improvement over fine-tuning in a fully supervised setting.</p>","PeriodicalId":73284,"journal":{"name":"IEEE International Conference on Healthcare Informatics. IEEE International Conference on Healthcare Informatics","volume":"2023 ","pages":"690-691"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11811837/pdf/","citationCount":"0","resultStr":"{\"title\":\"Identification of Offensive Language in Social Media Using Prompt Learning.\",\"authors\":\"Leilei Su, Yifan Peng, Zezheng Wang, Cong Sun\",\"doi\":\"10.1109/ichi57859.2023.00122\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Offensive language refers to the use of language in a manner that may offend or harm others who are within earshot or view in a public place. Given the importance of identifying such language in social media for promoting emotional well-being, we propose a prompt learning method and compare its performance with fine-tuning on two widely used datasets, HatEval and OffensEval. Experimental results demonstrate that prompt learning can achieve a performance improvement over fine-tuning in a fully supervised setting.</p>\",\"PeriodicalId\":73284,\"journal\":{\"name\":\"IEEE International Conference on Healthcare Informatics. IEEE International Conference on Healthcare Informatics\",\"volume\":\"2023 \",\"pages\":\"690-691\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11811837/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE International Conference on Healthcare Informatics. IEEE International Conference on Healthcare Informatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ichi57859.2023.00122\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2023/12/11 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE International Conference on Healthcare Informatics. IEEE International Conference on Healthcare Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ichi57859.2023.00122","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/12/11 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
Identification of Offensive Language in Social Media Using Prompt Learning.
Offensive language refers to the use of language in a manner that may offend or harm others who are within earshot or view in a public place. Given the importance of identifying such language in social media for promoting emotional well-being, we propose a prompt learning method and compare its performance with fine-tuning on two widely used datasets, HatEval and OffensEval. Experimental results demonstrate that prompt learning can achieve a performance improvement over fine-tuning in a fully supervised setting.