Cyberbullying Detection in Twitter using Language Extraction based Simplified Support Vector Machine (SSVM) Classifier
Journal Title: International Journal of Computer Science and Engineering - Year 2017, Vol 6, Issue 3
Abstract
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.
Authors and Affiliations
SHERLY T. T, B. ROSILINE JEETHA
Keywords
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