Publication: An evaluation of writeprint matching method to identify the authors of Thai online messages
Issued Date
2015-08-03
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2-s2.0-84947087717
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Mahidol University
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SCOPUS
Bibliographic Citation
2015 IEEE/ACIS 16th International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2015 - Proceedings. (2015)
Suggested Citation
Rangsipan Marukatat, Siravich Khongrod An evaluation of writeprint matching method to identify the authors of Thai online messages. 2015 IEEE/ACIS 16th International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2015 - Proceedings. (2015). doi:10.1109/SNPD.2015.7176200 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/35809
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Title
An evaluation of writeprint matching method to identify the authors of Thai online messages
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Abstract
© 2015 IEEE. This research studies the author identification of Thai online messages, based on 54 writing attributes. The method in focus is writeprint matching, which employs frequent pattern mining to create the writeprint of each suspect and computes a similarity score between this writeprint and the pattern found in an anonymous message. It achieved an average accuracy of 82%, while other well-known methods, support vector machine (SVM) and C4.5 decision tree, achieved average accuracies of 89% and 81%, respectively. As for the identification of individual author, all three methods were as good as each other in most cases. The writeprint matching method had potential in reducing Type I error or the chance of dismissing real offenders. However, its performance was still limited when the suspects had too similar writing styles.