Paper Key : IRJ************740
Author: Meghana R B,Meghana K B
Date Published: 05 Sep 2023
Most individuals now use communal complex spot as branch of their daily lives. Every day, a huge no of users create sketch on societal networking sites and engage with others regardless of their location or time. communal group check not barely bring benefits to users, but also security concerns for users and their information. To determine who is inciting threats in social networks, we must categorize the individualssocial network profiles. The categorization allows us to distinguish between authentic and phony communal medium shape. Traditionally, several sorting approach have been used to detect false profiles on social networks. However, we must enhance the accuracy rate of the In social networks, fakeprofile detection is possible. In this research, we propose Device Wisdom and natural language processing (NLP) strategies to increase the detection accuracy of bogus profiles. The Support Vector Machine (SVM) and the Nave Bayes method can be utilize.
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