Chat mining for gender prediction

Date
2006-10
Advisor
Instructor
Source Title
4th International Conference on Advances in Information Systems, ADVIS 2006
Print ISSN
0302-9743
Electronic ISSN
Publisher
Springer
Volume
Issue
Pages
274 - 283
Language
English
Type
Conference Paper
Journal Title
Journal ISSN
Volume Title
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. © Springer-Verlag Berlin Heidelberg 2006.

Course
Other identifiers
Book Title
Keywords
Classification (of information), Information retrieval, Linguistics, Problem solving, Text processing, Chat messages, Chat mining, Gender prediction, Information analysis
Citation
Published Version (Please cite this version)