Dong, Haichao; Hui, Siu Cheung and He, Yulan
(2006).
| DOI (Digital Object Identifier) Link: | http://doi.org/10.1108/14684520610706398 |
|---|---|
| Google Scholar: | Look up in Google Scholar |
Abstract
Purpose – The purpose of this research is to study the characteristics of chat messages from analysing a collection of 33,121 sample messages gathered from 1,700 sessions of conversations of 72 pairs of MSN Messenger users over a four month duration from June to September of 2005. The primary objective of chat message characterization is to understand the properties of chat messages for effective message analysis, such as message topic detection.
Design/methodology/approach – From the study on chat message characteristics, an indicative term-based categorization approach for chat topic detection is proposed. In the proposed approach, different techniques such as sessionalisation of chat messages and extraction of features from icon texts and URLs are incorporated for message pre-processing. Naı¨ve Bayes, Associative Classification, and Support Vector Machine are employed as classifiers for categorizing topics from chat sessions.
Findings – Indicative term-based approach is superior to the traditional document frequency based approach, for feature selection in chat topic categorization.
Originality/value – This paper studies the characteristics of chat messages and proposes an indicative term-based categorization approach for chat topic detection.
| Item Type: | Journal Article |
|---|---|
| Copyright Holders: | 2006 Emerald Group Publishing Limited |
| ISSN: | 1468-4527 |
| Keywords: | Communication; structural analysis; control systems; |
| Academic Unit/Department: | Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi) Faculty of Science, Technology, Engineering and Mathematics (STEM) |
| Interdisciplinary Research Centre: | Centre for Research in Computing (CRC) |
| Item ID: | 28562 |
| Depositing User: | Kay Dave |
| Date Deposited: | 19 Apr 2011 10:33 |
| Last Modified: | 02 Aug 2016 14:01 |
| URI: | http://oro.open.ac.uk/id/eprint/28562 |
| Share this page: |     |
Altmetrics | Scopus Citations |