Textual and contextual patterns for sentiment analysis over microblogs

Aisopos, F; Papadakis, G; Tserpes, K; Varvarigou, T

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	https://dspace.lib.ntua.gr/xmlui/handle/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