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dc.contributor.authorOelke, Danielaen_US
dc.contributor.authorGeißelmann, Bennoen_US
dc.contributor.authorKeim, Daniel A.en_US
dc.contributor.editorKresimir Matkovic and Giuseppe Santuccien_US
dc.date.accessioned2013-11-08T10:21:28Z
dc.date.available2013-11-08T10:21:28Z
dc.date.issued2012en_US
dc.identifier.isbn978-3-905673-89-0en_US
dc.identifier.urihttp://dx.doi.org/10.2312/PE/EuroVAST/EuroVA12/049-053en_US
dc.description.abstractMost state-of-the-art opinion and sentiment analysis techniques were developed for customer feedback data or reviews. Applying them to another domain is often not possible because the algorithms are based on the assumption that the opinions are expressed explicitly in the text. However, news articles, for instance, convey an opinion in a more subtle manner. In this work we analyze German soccer articles with respect to the sentiment that is expressed in them. Besides adapting conventional sentiment analysis algorithms to the specific domain, we also investigate what can be measured with these techniques and what should be measured on news articles according to communication scientists. We suggest to bridge the existing gap with visual analytics methods and demonstrate the usability of the techniques on a concrete application example.en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectCategories and Subject Descriptors (according to ACM CCS): Document and Text Processing [I.7.5]: Document Capture-Document Analysisen_US
dc.titleVisual Analysis of Explicit Opinion and News Bias in German Soccer Articlesen_US
dc.description.seriesinformationEuroVA 2012: International Workshop on Visual Analyticsen_US


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