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dc.contributor.authorAHMAD, KHURSHID
dc.contributor.editorGerhard, Heyeren
dc.date.accessioned2009-04-03T14:20:46Z
dc.date.available2009-04-03T14:20:46Z
dc.date.created23 March 2009en
dc.date.issued2009
dc.date.submitted2009en
dc.identifier.citationRobert Remus, Gerhard Heyer and Khurshid Ahmad `Sentiment in German language news and blogs, and the DAX' in proceedings of Text Mining Services 2009, Leipzig, Germany, 23 March 2009, Gerhard Heyer (ed), Leipziger Beitrage zur Informatik, 2009, pp 149 - 158en
dc.identifier.otherY
dc.identifier.otherYen
dc.identifier.urihttp://hdl.handle.net/2262/28766
dc.descriptionPUBLISHEDen
dc.description.abstractAn analysis of a diachronically organised corpus of Germanlanguage newspaper articles and blog posts on economy and finance is presented using a prototype dictionary of affect in German. The changes in the frequency of occurrence of positive and negative polarity words are rendered as return time series and the properties of this time series are described. The returns and the variance of returns show that the time series of affect words share a number of properties with that of financial time series in general and in particular with a contemporaneous time series of the DAX ? the German stock exchange index. Both the series have outliers not predicted by a normal distribution. Our analysis is a starting point for studying the impact of news and blogs on financial instruments and vice versa.en
dc.format.extent149en
dc.format.extent158en
dc.format.extent213339 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.publisherLeipziger Beitrage zur Informatiken
dc.rightsYen
dc.subjectComputer Scienceen
dc.titleSentiment in German language news and blogs, and the DAXen
dc.typeConference Paperen
dc.type.supercollectionscholarly_publicationsen
dc.type.supercollectionrefereed_publicationsen
dc.identifier.peoplefinderurlhttp://people.tcd.ie/kahmad
dc.identifier.rssinternalid56409


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