Identifying and Detecting Offensive Language in Social Media
Boddu SriLatha1, Srinivasa Bapiraju Gadiraju2

1SriLatha Boddu,PG Scholor, M.Tech, Computer Science and Engineering Department of CSE, Gokaraju Rangaraju Institiute of Engineering and Technology, (GRIET), Hyderabad, India.
2Dr.Srinivasa Bapiraju Gadiraju,, Professor, Department of CSE, Gokaraju Rangaraju Institiute of Engineering and Technology, (GRIET), Hyderabad, India.

Manuscript received on 30 June 2019 | Revised Manuscript received on 05 July 2019 | Manuscript published on 30 July 2019 | PP: 1359-1362| Volume-8 Issue-9, July 2019 | Retrieval Number :I7524078919/19©BEIESP | DOI: 10.35940/ijitee.I7524.078919
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Abstract: The utilization of the social media destinations is developing quickly to interface with the networks and to share the thoughts among others. It might happen that a large portion of the general population disdain the thoughts of others individual perspectives and utilize their posts. Because of these hostile terms, numerous individuals particularly youth and young people endeavor to embrace which may fundamentally influence the others individual are honest personalities. As hostile terms progressively use by the general population in profoundly way, it is hard to discover or characterize such hostile terms in genuine day-to-day life. To defeat from this issue, the proposed system dissects the offensive words and can group the hostile sentence on a specific topic dialog utilizing the SVM as managed arrangement in the information mining. The proposed system additionally can locate the potential client by methods for which the hostile language spread among others and characterize the proportional analysis of SVM with Naive Bayes procedure. The proposed structure goes about as a screening instrument that cautions the customer about such messages.
Keywords: cyber bullying, adolescent safety, offensive languages, social media.

Scope of the Article: Large-Scale Cyber Systems