Gender-Preferential Text Mining of E-mail Discourse

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18th Annual Computer Security Applications Conference (ACSAC '02)

San Diego California

December 09-December 13

ISBN: 0-7695-1828-1

	ASCII Text	x
	Malcolm Corney, Olivier de Vel, Alison Anderson, George Mohay, "Gender-Preferential Text Mining of E-mail Discourse," Computer Security Applications Conference, Annual, pp. 282, 18th Annual Computer Security Applications Conference (ACSAC '02), 2002.

	BibTex	x
	@article{ 10.1109/CSAC.2002.1176299, author = {Malcolm Corney and Olivier de Vel and Alison Anderson and George Mohay}, title = {Gender-Preferential Text Mining of E-mail Discourse}, journal ={Computer Security Applications Conference, Annual}, volume = {0}, year = {2002}, issn = {1063-9527}, pages = {282}, doi = {http://doi.ieeecomputersociety.org/10.1109/CSAC.2002.1176299}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Computer Security Applications Conference, Annual TI - Gender-Preferential Text Mining of E-mail Discourse SN - 1063-9527 SP EP A1 - Malcolm Corney, A1 - Olivier de Vel, A1 - Alison Anderson, A1 - George Mohay, PY - 2002 KW - null VL - 0 JA - Computer Security Applications Conference, Annual ER -

Malcolm Corney, Queensland University of Technology

Olivier de Vel, Defence Science and Technology Organisation

Alison Anderson, Queensland University of Technology

George Mohay, Queensland University of Technology

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CSAC.2002.1176299

This paper describes an investigation of authorship gender attribution mining from e-mail text documents. We used an extended set of predominantly topic content-free e-mail document features such as style markers, structural characteristics and gender-preferential language features together with a Support Vector Machine learning algorithm. Experiments using a corpus of e-mail documents generated by a large number of authors of both genders gave promising results for author gender categorisation.

Citation:

Malcolm Corney, Olivier de Vel, Alison Anderson, George Mohay, "Gender-Preferential Text Mining of E-mail Discourse," acsac, pp.282, 18th Annual Computer Security Applications Conference (ACSAC '02), 2002

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