{"title":"从网络闲聊中提取基金投资者情绪","authors":"Bo Wang, Xianfeng Liu, Zhong Pu","doi":"10.1109/ICCIS.2010.150","DOIUrl":null,"url":null,"abstract":"Reviews on Web can help small investors make decision in selecting funds. The size of fund reviews is smaller than other products, which proposes a challenge to extract sentiment by using statistic methods. We develop a methodology to deal with this problem by using association rule to select seed words and introducing new outside resources to improve the traditional PMI performance. The result shows that this methodology is effective.","PeriodicalId":227848,"journal":{"name":"2010 International Conference on Computational and Information Sciences","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Extracting Sentiment of Fund Investors from Small Talk on the Web\",\"authors\":\"Bo Wang, Xianfeng Liu, Zhong Pu\",\"doi\":\"10.1109/ICCIS.2010.150\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Reviews on Web can help small investors make decision in selecting funds. The size of fund reviews is smaller than other products, which proposes a challenge to extract sentiment by using statistic methods. We develop a methodology to deal with this problem by using association rule to select seed words and introducing new outside resources to improve the traditional PMI performance. The result shows that this methodology is effective.\",\"PeriodicalId\":227848,\"journal\":{\"name\":\"2010 International Conference on Computational and Information Sciences\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-12-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 International Conference on Computational and Information Sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCIS.2010.150\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 International Conference on Computational and Information Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCIS.2010.150","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Extracting Sentiment of Fund Investors from Small Talk on the Web
Reviews on Web can help small investors make decision in selecting funds. The size of fund reviews is smaller than other products, which proposes a challenge to extract sentiment by using statistic methods. We develop a methodology to deal with this problem by using association rule to select seed words and introducing new outside resources to improve the traditional PMI performance. The result shows that this methodology is effective.
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