{"id":148249,"date":"2006-01-01T00:00:00","date_gmt":"2006-01-01T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/determining-term-subjectivity-and-term-orientation-for-opinion-mining\/"},"modified":"2018-10-16T20:50:49","modified_gmt":"2018-10-17T03:50:49","slug":"determining-term-subjectivity-and-term-orientation-for-opinion-mining","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/determining-term-subjectivity-and-term-orientation-for-opinion-mining\/","title":{"rendered":"Determining Term Subjectivity and Term Orientation for Opinion Mining"},"content":{"rendered":"<div class=\"asset-content\">\n<p>Opinion mining is a recent subdiscipline of computational linguistics which is concerned not with the topic a document is about, but with the opinion it expresses. To aid the extraction of opinions from text, recent work has tackled the issue of determining the orientation of &#8220;subjective&#8221; terms contained in text, i.e. deciding whether a term that carries opinionated content has a positive or a negative connotation. This is believed to be of key importance for identifying the orientation of documents, i.e. determining whether a document expresses a positive or negative opinion about its subject matter. We contend that the plain determination of the orientation of terms is not a realistic problem, since it starts from the nonrealistic assumption that we already know whether a term is subjective or not; this would imply that a linguistic resource that marks terms as &#8220;subjective&#8221; or &#8220;objective&#8221; is available, which is usually not the case. In this paper we confront the task of deciding whether a given term has a positive connotation, or a negative connotation, or has no subjective connotation at all; this problem thus subsumes the problem of determining subjectivity and the problem of determining orientation. We tackle this problem by testing three different variants of a semi-supervised method previously proposed for orientation detection. Our results show that determining subjectivity and orientation is a much harder problem than determining orientation alone.<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Opinion mining is a recent subdiscipline of computational linguistics which is concerned not with the topic a document is about, but with the opinion it expresses. To aid the extraction of opinions from text, recent work has tackled the issue of determining the orientation of &#8220;subjective&#8221; terms contained in text, i.e. deciding whether a term [&hellip;]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr-author-ordering":null,"msr_publishername":"","msr_publisher_other":"","msr_booktitle":"Proceedings EACL-06, the 11rd Conference of the European Chapter of the Association for Computational Linguistics","msr_chapter":"","msr_edition":"Proceedings EACL-06, the 11rd Conference of the European Chapter of the Association for Computational 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