Chat mining for gender prediction
Source:
Lecture Notes in Computer Science, Springer, Volume 4243, Izmir, Turkey, p.274-283 (2006)
ISBN:
978-3-540-23526-2
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.
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