Chat mining for gender prediction
Source:
Lecture Notes in Computer Science, Volume 3280, p.801-809 (2006)
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.
