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dc.contributor.authorDevitt, Annen
dc.contributor.authorAHMAD, KHURSHIDen
dc.date.accessioned2008-12-04T17:16:12Z
dc.date.available2008-12-04T17:16:12Z
dc.date.created25-27 Juneen
dc.date.issued2007en
dc.date.submitted2007en
dc.identifier.citationAnn Devitt and Khurshid Ahmad, Sentiment Polarity Identification in Financial News: A Cohesion-based Approach, Annual Meeting of the Association of Computational Linguistics (ACL 2007), Prague, Czech Republic, 25-27 June, 2007en
dc.identifier.otherYen
dc.identifier.urihttp://hdl.handle.net/2262/25729
dc.descriptionPUBLISHEDen
dc.descriptionPrague, Czech Republicen
dc.description.abstractText is not unadulterated fact. A text can make you laugh or cry but can it also make you short sell your stocks in company A and buy up options in company B? Research in the domain of finance strongly suggests that it can. Studies have shown that both the informational and affective aspects of news text affect the markets in profound ways, impacting on volumes of trades, stock prices, volatility and even future firm earnings. This paper aims to explore a computable metric of positive or negative polarity in financial news text which is consistent with human judgments and can be used in a quantitative analysis of news sentiment impact on financial markets. Results from a preliminary evaluation are presented and discussed.en
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.rightsYen
dc.subjectSentiment Analysisen
dc.subjectLexical Cohesionen
dc.titleSentiment Polarity Identification in Financial News: A Cohesion-based Approachen
dc.title.alternativeAnnual Meeting of the Association of Computational Linguistics (ACL 2007)en
dc.typeConference Paperen
dc.type.supercollectionscholarly_publicationsen
dc.type.supercollectionrefereed_publicationsen
dc.identifier.peoplefinderurlhttp://people.tcd.ie/devittanen
dc.identifier.peoplefinderurlhttp://people.tcd.ie/kahmaden
dc.identifier.rssinternalid54148en
dc.subject.TCDThemeIntelligent Content & Communicationsen


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