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A malicious-comment detection technique on the internet using the support vector machine

Authors
최재현박제원Hong, J.
Issue Date
Jun-2016
Publisher
International Information Institute Ltd.
Keywords
Classification; Data mining; Korean normalization; Learning machine; Morphological analyzer; Sentiment analysis; Sentiment dictionary
Citation
Information (Japan), v.19, no.6B, pp.2383 - 2389
Journal Title
Information (Japan)
Volume
19
Number
6B
Start Page
2383
End Page
2389
URI
http://scholarworks.bwise.kr/ssu/handle/2018.sw.ssu/5675
ISSN
1343-4500
Abstract
The comment system on the Internet was started to facilitate the exchange of information from one person to another online. Vicious users, however, have been taking advantage of the anonymity on the Internet, aggressively issuing comments for defamation, privacy violation, and other negative purposes. In this paper, to solve this problem, a technique of detecting malicious comments that can contribute to a sound cyber ecosystem is proposed. The proposed technique has a five-step process: data collection, Korean normalization, sentiment dictionary construction, sentiment analysis, and deduction of an equation for malicious-comment detection using SVM (support vector machine) and a training dataset. To verify the effectiveness of the proposed method, its performance was assessed using a valuation data set, and the experiment results showed 87.8% accuracy, higher than that shown in the previous relevant studies. © 2016 International Information Institute.
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