Küçükyılmaz, TayfunCambazoğlu, B. BarlaAykanat, CevdetCan, Fazlı2016-02-082016-02-082006-100302-9743http://hdl.handle.net/11693/27262Date of Conference: 18-20 October, 2006Conference name: 4th International Conference on Advances in Information Systems, ADVIS 2006The 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.EnglishClassification (of information)Information retrievalLinguisticsProblem solvingText processingChat messagesChat miningGender predictionInformation analysisConference Paper10.1007/11890393_29