{"title":"挖掘Twitter的细粒度政治观点极性分类、意识形态检测和讽刺检测","authors":"Sandeepa Kannangara","doi":"10.1145/3159652.3170461","DOIUrl":null,"url":null,"abstract":"In this paper, we propose three models for socio-political opinion polarity classification of microblog posts. Firstly, a novel probabilistic model, Joint-Entity-Sentiment-Topic (JEST) model, which captures opinions as a combination of the target entity, sentiment and topic, will be proposed. Secondly, a model for ideology detection called JEST-Ideology will be proposed to identify an individual»s orientation towards topics/issues and target entities by extending the proposed opinion polarity classification framework. Finally, we propose a novel method to accurately detect sarcastic opinions by utilizing detected fine-grained opinion and ideology.","PeriodicalId":401247,"journal":{"name":"Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"32","resultStr":"{\"title\":\"Mining Twitter for Fine-Grained Political Opinion Polarity Classification, Ideology Detection and Sarcasm Detection\",\"authors\":\"Sandeepa Kannangara\",\"doi\":\"10.1145/3159652.3170461\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose three models for socio-political opinion polarity classification of microblog posts. Firstly, a novel probabilistic model, Joint-Entity-Sentiment-Topic (JEST) model, which captures opinions as a combination of the target entity, sentiment and topic, will be proposed. Secondly, a model for ideology detection called JEST-Ideology will be proposed to identify an individual»s orientation towards topics/issues and target entities by extending the proposed opinion polarity classification framework. Finally, we propose a novel method to accurately detect sarcastic opinions by utilizing detected fine-grained opinion and ideology.\",\"PeriodicalId\":401247,\"journal\":{\"name\":\"Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining\",\"volume\":\"2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-02-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"32\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3159652.3170461\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3159652.3170461","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Mining Twitter for Fine-Grained Political Opinion Polarity Classification, Ideology Detection and Sarcasm Detection
In this paper, we propose three models for socio-political opinion polarity classification of microblog posts. Firstly, a novel probabilistic model, Joint-Entity-Sentiment-Topic (JEST) model, which captures opinions as a combination of the target entity, sentiment and topic, will be proposed. Secondly, a model for ideology detection called JEST-Ideology will be proposed to identify an individual»s orientation towards topics/issues and target entities by extending the proposed opinion polarity classification framework. Finally, we propose a novel method to accurately detect sarcastic opinions by utilizing detected fine-grained opinion and ideology.
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