Using text mining algorithm to detect gender deception based on Malaysian chatroom lingo / Dianne L.M. Cheong and Nur Atiqah Sia Abdullah@Sia Sze Yieng

E-mail is used for communication between strangers and friends. It can be a fantasy playground for identity experimentations where players take on an imaginary persona and interact with each other in the virtual world. In communication, knowing the identity of those whom you communicate is essential...

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Bibliographic Details
Main Authors: L., Dianne M. Cheong, Sia Abdullah, Nur Atiqah
Format: Research Reports
Language:English
Published: 2006
Subjects:
Online Access:https://ir.uitm.edu.my/id/eprint/49538/1/49538.pdf
https://ir.uitm.edu.my/id/eprint/49538/
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Institution: Universiti Teknologi Mara
Language: English
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Summary:E-mail is used for communication between strangers and friends. It can be a fantasy playground for identity experimentations where players take on an imaginary persona and interact with each other in the virtual world. In communication, knowing the identity of those whom you communicate is essential for understanding and evaluating an interaction. However, the presentation of self in the virtual world is often a conscious and deliberate endeavour. Therefore, gender deception is difficult and risky and it can be abandoned at will. Inference can be made both from writing style and from clues hidden in the posting data. A text-mining algorithm was designed to detect gender deception based on gender-preferential features at the word or clause level of Malaysian e-mail users. Based on this designed text algorithm, a prototype in Visual Basic is developed. The prototype was tested with 16 documents; each consists of 5 e-mails exchanges of respective individuals. Out tests have shown that the prototype is at 81.3% of accuracy level. This is consistent with a human reader of the documents. The tested prototype will be a tool to assist interest parties such as the Criminology and Forensic Department, e-mail users and virtual communities to successfully identify gender deception.