Social media platform are growing day by day because people are taking lots of interest in social life so the people spend their most of the time on smartphones, online dating, blogs, chat rooms, Facebook and Twitter. 

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Impact of SMOTE on Imbalanced Text Features for Toxic Comments Classification using RVVC Model”. This research can detect the abusing and toxic content automatically with high efficiency and accuracy on online platforms with 97% accuracy and can help this platform to control online abuse. Vaibhav Rupapara and Furqan Rustam think that their system is too strong and they can provide their approach to online social media platforms voluntarily to stop abuse and toxic conversation. In this research, other team members were Ms. Hina Fatima Shahzad, Dr. Imran Ashraf (South Korea), Dr. Arif Mehmood (Pakistan), and Prof. Dr. Gyu Sang Choi (South Korea). https://doi.org/10.1109/ACCESS.2021.3083638. This work was supported in part by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education under Grant NRF-2019R1A2C1006159, and in part by the Ministry of Science and ICT (MSIT), South Korea, through the Information Technology Research Center (ITRC) support program supervised by the Institute for Information and communications Technology Promotion (IITP) under Grant IITP-2021-2016-0-00313.

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