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 classi?cation 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 e?ect of gender on the writing style is discussed.
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