Yang Liu, Xiaohui Yu, Zhongshuai Chen, Bingbing Liu
{"title":"情态句的情感分析","authors":"Yang Liu, Xiaohui Yu, Zhongshuai Chen, Bingbing Liu","doi":"10.1145/2513549.2513556","DOIUrl":null,"url":null,"abstract":"This paper is concerned with sentiment analysis of sentences with modality. Modality is a commonly occuring linguistic phenomenon. Due to its special characteristics, the sentiment borne by modality may be hard to determine by existing methods. We first present a linguistic analysis of modality, and then identify some valuable features to train a support vector machine classifier to determine the sentiment orientation of such sentences. We show experimental results on sentences with modality that are extracted from the reviews of four different products to illustrate the effectiveness of the proposed method.","PeriodicalId":126426,"journal":{"name":"Proceedings of the 2013 international workshop on Mining unstructured big data using natural language processing","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"38","resultStr":"{\"title\":\"Sentiment analysis of sentences with modalities\",\"authors\":\"Yang Liu, Xiaohui Yu, Zhongshuai Chen, Bingbing Liu\",\"doi\":\"10.1145/2513549.2513556\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper is concerned with sentiment analysis of sentences with modality. Modality is a commonly occuring linguistic phenomenon. Due to its special characteristics, the sentiment borne by modality may be hard to determine by existing methods. We first present a linguistic analysis of modality, and then identify some valuable features to train a support vector machine classifier to determine the sentiment orientation of such sentences. We show experimental results on sentences with modality that are extracted from the reviews of four different products to illustrate the effectiveness of the proposed method.\",\"PeriodicalId\":126426,\"journal\":{\"name\":\"Proceedings of the 2013 international workshop on Mining unstructured big data using natural language processing\",\"volume\":\"23 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-10-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"38\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2013 international workshop on Mining unstructured big data using natural language processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2513549.2513556\",\"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 2013 international workshop on Mining unstructured big data using natural language processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2513549.2513556","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper is concerned with sentiment analysis of sentences with modality. Modality is a commonly occuring linguistic phenomenon. Due to its special characteristics, the sentiment borne by modality may be hard to determine by existing methods. We first present a linguistic analysis of modality, and then identify some valuable features to train a support vector machine classifier to determine the sentiment orientation of such sentences. We show experimental results on sentences with modality that are extracted from the reviews of four different products to illustrate the effectiveness of the proposed method.