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