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http://dx.doi.org/10.4275/KSLIS.2013.47.1.269

Automatic Classification of Malicious Usage on Twitter  

Kim, Meen Chul (연세대학교 문헌정보학과 대학원)
Shim, Kyu Seung (연세대학교 문헌정보학과)
Han, Nam Gi (연세대학교 문헌정보학과)
Kim, Ye Eun (연세대학교 문헌정보학과)
Song, Min (연세대학교 문헌정보학과)
Publication Information
Journal of the Korean Society for Library and Information Science / v.47, no.1, 2013 , pp. 269-286 More about this Journal
Abstract
The advent of Web 2.0 and social media is taking a leading role of emerging big data. At the same time, however, informational dysfunction such as infringement of one's rights and violation of social order has been increasing sharply. This study, therefore, aims at defining malicious usage, identifying malicious feature, and devising an automated method for classifying them. In particular, the rule-based experiment reveals statistically significant performance enhancement.
Keywords
Social Media Mining; Twitter; Malicious Usage; Automatic Classification;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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