Chat mining for gender prediction

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buir.contributor.authorAykanat, Cevdet
dc.citation.epage283en_US
dc.citation.spage274en_US
dc.contributor.authorKüçükyılmaz, Tayfunen_US
dc.contributor.authorCambazoğlu, B. Barlaen_US
dc.contributor.authorAykanat, Cevdeten_US
dc.contributor.authorCan, Fazlıen_US
dc.coverage.spatialIzmir, Turkey
dc.date.accessioned2016-02-08T11:49:03Z
dc.date.available2016-02-08T11:49:03Z
dc.date.issued2006-10en_US
dc.departmentDepartment of Computer Engineeringen_US
dc.descriptionDate of Conference: 18-20 October, 2006
dc.descriptionConference name: 4th International Conference on Advances in Information Systems, ADVIS 2006
dc.description.abstractThe aim of this paper is to investigate the feasibility of predicting the gender of a text document's author using linguistic evidence. For this purpose, term- and style-based classification techniques are evaluated over a large collection of chat messages. Prediction accuracies up to 84.2% are achieved, illustrating the applicability of these techniques to gender prediction. Moreover, the reverse problem is exploited, and the effect of gender on the writing style is discussed. © Springer-Verlag Berlin Heidelberg 2006.en_US
dc.description.provenanceMade available in DSpace on 2016-02-08T11:49:03Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 70227 bytes, checksum: 26e812c6f5156f83f0e77b261a471b5a (MD5) Previous issue date: 2006en
dc.identifier.doi10.1007/11890393_29en_US
dc.identifier.issn0302-9743
dc.identifier.urihttp://hdl.handle.net/11693/27262
dc.language.isoEnglishen_US
dc.publisherSpringeren_US
dc.relation.isversionofhttps://doi.org/10.1007/11890393_29en_US
dc.source.title4th International Conference on Advances in Information Systems, ADVIS 2006en_US
dc.subjectClassification (of information)en_US
dc.subjectInformation retrievalen_US
dc.subjectLinguisticsen_US
dc.subjectProblem solvingen_US
dc.subjectText processingen_US
dc.subjectChat messagesen_US
dc.subjectChat miningen_US
dc.subjectGender predictionen_US
dc.subjectInformation analysisen_US
dc.titleChat mining for gender predictionen_US
dc.typeConference Paperen_US

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