Chat mining for gender prediction

Tayfun Kucukyilmaz*, B. Barla Cambazoglu, Cevdet Aykanat, Fazli Can

*Corresponding author for this work

Research output: Chapter/Conference proceedingConference proceedingAcademicpeer-review

51 Citations (Scopus)


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.

Original languageEnglish
Title of host publicationAdvances in Information Systems - 4th International Conference, ADVIS 2006, Proceedings
Number of pages10
Publication statusPublished - 2006
Externally publishedYes
Event4th International Conference on Advances in Information Systems, ADVIS 2006 - Izmir, Turkey
Duration: 18 Oct 200620 Oct 2006

Publication series

SeriesLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4243 LNCS


Conference4th International Conference on Advances in Information Systems, ADVIS 2006


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