• Prashant Jagtap
• Prof. Lalita Randive

One of the fundamental challenges faced by Social Media Platforms (SMP) is the ability to restrict messages posting, in order to avoid unwanted messages from getting displayed. Another challenge is give users the ability to control the contents posted on their own private space to. Today's Social Media Platforms provide very little when it comes to controlling of contents. In this paper, we propose a method to be implementing in SMP allowing it's users to have a direct control on the messages posted on their walls. This is achieved through a flexible rule-based system, that allows users to customize the filtering criteria to be applied to their walls, and Machine Learning based soft classifier automatically labeling messages in support of content-based filtering.

"Implementing Naïve Bayes Classification to Identify Intrusive and Offensive Text on Social Media Platform ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 12, page no.d572-d578, December-2021, Available :http://www.jetir.org/papers/JETIR2112367.pdf

"Implementing Naïve Bayes Classification to Identify Intrusive and Offensive Text on Social Media Platform ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 12, page no. ppd572-d578, December-2021, Available at : http://www.jetir.org/papers/JETIR2112367.pdf