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  • 标题:Cyberbullying Detection in Twtter using Language Extraction Based Simplified Support Vector Machine (SSVM) Classifier
  • 本地全文:下载
  • 作者:Sherly T.T ; B. Rosiline Jeetha
  • 期刊名称:International Journal of Computer Science and Engineering
  • 印刷版ISSN:2278-9960
  • 电子版ISSN:2278-9979
  • 出版年度:2017
  • 卷号:6
  • 期号:3
  • 页码:21-30
  • 语种:English
  • 出版社:IASET Journals
  • 摘要:Text mining is the thrust research area in the field of data mining and knowledge engineering. The communication data commencing online social networks is capable enough to offer new insights for building societies that was earlier thought as impossible in terms of scale and extent. Cyberbullying is a common thing in social networks like twitter which is described as the use of information and communication technology by an individual or a group of users to annoy other users. This research work presents cyberbullying detection in twitter using language extraction and simplified support vector machine classifier. Around 4556 tweets are taken from the Twitter. The proposed SSVM classifier allowed to train with 3000 tweets. The SSVM is compared with existing SVM classifier. Simulations are carried out using MATLAB 2012. The result shows that the proposed language extraction based SSVM outperforms than that of the existing classifier.
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