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Sentence Abusive Detection using Text Mining

A. Habiba, J.I. Sheeba


Text mining is the significant aspects of study and research motivated by the remarkable growth of the social web. Cyber bully is a major problem that occurs in the online communications. Nowadays, methods for automatic thoughts mining on online data are becoming increasingly important. In this proposal, we studied about the detection of the general cyber bully polarity. A thorough analysis has been made for sentiment (i.e.) opinion mining but the cyber bullies which harass and threatens the online social victims research work has not been done as familiar. The aim of this paper is to extract cyber bully polarity from blog messages with methods of pre-processing, frequency measure and Classifier algorithm. The novelty of this paper arise from treating user generated content on blogs as dynamically evolving linked documents that vary by thoughts, content and emotions.


Text Mining, Cyber Bully, Classification, Classifier Algorithm, Abusive Detection.

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