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Summary: Chat mining: Predicting user and message attributes
in computer-mediated communication
Tayfun Kucukyilmaz a
, B. Barla Cambazoglu b
, Cevdet Aykanat a,*, Fazli Can a
a
Computer Engineering Department, Bilkent University, TR 06800 Bilkent, Ankara, Turkey
b
Yahoo! Research Barcelona, Barcelona, Spain
Received 1 August 2007; received in revised form 14 December 2007; accepted 29 December 2007
Available online 4 March 2008
Abstract
The focus of this paper is to investigate the possibility of predicting several user and message attributes in text-based,
real-time, online messaging services. For this purpose, a large collection of chat messages is examined. The applicability of
various supervised classification techniques for extracting information from the chat messages is evaluated. Two competing
models are used for defining the chat mining problem. A term-based approach is used to investigate the user and message
attributes in the context of vocabulary use while a style-based approach is used to examine the chat messages according to
the variations in the authors' writing styles. Among 100 authors, the identity of an author is correctly predicted with 99.7%
accuracy. Moreover, the reverse problem is exploited, and the effect of author attributes on computer-mediated commu-
nications is discussed.
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