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dc.contributor.authorHsu, Wei-Yunen_US
dc.contributor.authorHsu, Hui-Huangen_US
dc.contributor.authorTseng, Vincent S.en_US
dc.date.accessioned2019-06-03T01:08:35Z-
dc.date.available2019-06-03T01:08:35Z-
dc.date.issued2019-05-01en_US
dc.identifier.issn1386-145Xen_US
dc.identifier.urihttp://dx.doi.org/10.1007/s11280-018-0561-6en_US
dc.identifier.urihttp://hdl.handle.net/11536/151955-
dc.description.abstractSocial media enables people to communicate with each other on the Internet in real-time and rich styles. In other words, there is a lot of information on the social media. If we can extract negative opinions of some brands, enterprises or politics, we can use these opinions to know the market demands and solve problems. In this paper, we propose a novel approach to extract negative-sentiment-oriented features and identify negative opinions in social media with text mining and machine learning techniques, support vector machine and neural network, as well as data collection with Web crawler. The experimental results show that our proposed methods can work effectively.en_US
dc.language.isoen_USen_US
dc.subjectsentiment analysisen_US
dc.subjecttext miningen_US
dc.subjectneural networken_US
dc.subjectsupport vector machineen_US
dc.titleDiscovering negative comments by sentiment analysis on web forumen_US
dc.typeArticleen_US
dc.identifier.doi10.1007/s11280-018-0561-6en_US
dc.identifier.journalWORLD WIDE WEB-INTERNET AND WEB INFORMATION SYSTEMSen_US
dc.citation.volume22en_US
dc.citation.issue3en_US
dc.citation.spage1297en_US
dc.citation.epage1311en_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:000466989400019en_US
dc.citation.woscount0en_US
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