Chat mining for gender prediction

Authors:
Tayfun Kucukyilmaz;B. Barla Cambazoglu;Cevdet Aykanat;Fazli Can
Affiliations:
Department of Computer Engineering, Bilkent University, Bilkent, Ankara, Turkey;Department of Computer Engineering, Bilkent University, Bilkent, Ankara, Turkey;Department of Computer Engineering, Bilkent University, Bilkent, Ankara, Turkey;Department of Computer Engineering, Bilkent University, Bilkent, Ankara, Turkey
Venue:
ADVIS'06 Proceedings of the 4th international conference on Advances in Information Systems
Year:
2006

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Abstract

The 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.