A Machine Learning based Preventing the Occurrence of Cyber Bullying Messages on OSN
K. Leela Prasad1, P. Anusha2, M. Srinivasa Rao3, K. Venkata Rao4
1Kaki Leela Prasad, Department of Information Technology, Vignan’s Institute of Information Technology, Visakhapatnam, India.
2Pilaka Anusha, Department of Computer Science Engineering, Vignan’s Institute of Information Technology, Visakhapatnam, India.
3MaradaSrinivasaa Rao, Department of Computer Science Engineering, Vignan’s Institute of Information Technology, Visakhapatnam, India.
4Dr.K.Venakata Rao, Department of Information Technology, Vignan’s Institute of Information Technology, Visakhapatnam, India.
Manuscript received on 05 March 2019 | Revised Manuscript received on 11 March 2019 | Manuscript published on 30 July 2019 | PP: 1861-1865 | Volume-8 Issue-2, July 2019 | Retrieval Number: A9164058119/19©BEIESP | DOI: 10.35940/ijrte.A9164.078219
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The process of threaten or harassment of any user with the help of posting wrong/abused or vulgar messages using the social media in the internet is known as Cyber bullying. These messages may sometime contain a text posted by a teen, or preteen or a child who want to threaten or harassed or embarrassed other child by posting the messages. So in this project, we mainly try to propose another depiction learning strategy to handle this issue known as SEMdae. Here the semantic augmentation comprises of predefined words that contain noise or abused meaning which is posted into the database by the admin and these words are classified based on the five categories that are available in the literature like “HATE, VULGAR, OFFENSIVE, SEX, and VOILENCE”.
Index Terms: BoW, SEMdae.
Scope of the Article: Machine Learning