BlogVox: Learning Sentiment Classifiers

dc.contributor.authorMartineau, Justin
dc.contributor.authorJava, Akshay
dc.contributor.authorKolari, Pranam
dc.contributor.authorJoshi, Anupam
dc.contributor.authorFinin, Tim
dc.contributor.authorMayfield, James
dc.date.accessioned2018-11-29T19:17:46Z
dc.date.available2018-11-29T19:17:46Z
dc.date.issued2007-07-22
dc.descriptionProceedings of the Twenty-Second AAAI Conference on Artificial Intelligenceen
dc.description.abstractPerforming sentiment analysis upon a topic, specified by key words, without prior knowledge about the key words is a difficult task. With the growth of the blogosphere researchers, corporations, and politicians, among others are very interested in applying sentiment detection to blogs. To accommodate the demands from myriad users, with similarly diverse desires, a sentiment analysis engine for blogs must discover domain specific features relevant to queries in order to accurately assess the sentiment of blogs. Using meta-learning upon the results of web searches, as BlogVox does, can accomplish this goal.en
dc.description.sponsorshipPartial support provided by IBM and by NSF awards ITR-IIS-0326460 and ITR-IDM-0219649.en
dc.description.urihttps://www.aaai.org/Papers/AAAI/2007/AAAI07-319.pdfen
dc.format.extent2 pagesen
dc.genreconference papers and proceedings preprintsen
dc.identifierdoi:10.13016/M2ZK55R01
dc.identifier.citationJustin Martineau, Akshay Java, Pranam Kolari, Anupam Joshi, Tim Finin, and James Mayfield, BlogVox: Learning Sentiment Classifiers, Proceedings of the Twenty-Second AAAI Conference on Artificial Intelligence, 2007, https://www.aaai.org/Papers/AAAI/2007/AAAI07-319.pdfen
dc.identifier.urihttp://hdl.handle.net/11603/12133
dc.language.isoenen
dc.publisherAAAIen
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Computer Science and Electrical Engineering Department Collection
dc.relation.ispartofUMBC Faculty Collection
dc.relation.ispartofUMBC Student Collection
dc.rightsThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.
dc.subjectBlogVoxen
dc.subjectSentimenten
dc.subjectClassifiersen
dc.subjectLearningen
dc.subjectUMBC Ebiquity Research Groupen
dc.titleBlogVox: Learning Sentiment Classifiersen
dc.typeTexten

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