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Textual and contextual patterns for sentiment analysis over microblogs

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dc.contributor.author Aisopos, F en
dc.contributor.author Papadakis, G en
dc.contributor.author Tserpes, K en
dc.contributor.author Varvarigou, T en
dc.date.accessioned 2014-03-01T02:54:02Z
dc.date.available 2014-03-01T02:54:02Z
dc.date.issued 2012 en
dc.identifier.uri http://hdl.handle.net/123456789/36551
dc.subject N-gram graphs en
dc.subject Sentiment analysis en
dc.subject Social context en
dc.subject Social media en
dc.subject.other Content-based en
dc.subject.other Context-based en
dc.subject.other Data sets en
dc.subject.other Inherent characteristics en
dc.subject.other Micro-blog en
dc.subject.other N-gram graphs en
dc.subject.other Sentiment analysis en
dc.subject.other Social context en
dc.subject.other Social media en
dc.subject.other Traditional techniques en
dc.subject.other World Wide Web en
dc.subject.other Data mining en
dc.title Textual and contextual patterns for sentiment analysis over microblogs en
heal.type conferenceItem en
heal.identifier.primary 10.1145/2187980.2188073 en
heal.identifier.secondary http://dx.doi.org/10.1145/2187980.2188073 en
heal.publicationDate 2012 en
heal.abstract Microblog content poses serious challenges to the applicability of sentiment analysis, due to its inherent characteristics. We introduce a novel method relying on content-based and context-based features, guaranteeing high effectiveness and robustness in the settings we are considering. The evaluation of our methods over a large Twitter data set indicates significant improvements over the traditional techniques. en
heal.journalName WWW'12 - Proceedings of the 21st Annual Conference on World Wide Web Companion en
dc.identifier.doi 10.1145/2187980.2188073 en
dc.identifier.spage 453 en
dc.identifier.epage 454 en


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