To analyze, who are encouraging threats in social network we need to classify the social networks profiles of the users. From the classification, we can get the genuine profiles and fake profiles on the social networks. Traditionally, we have different classification methods for detecting the fake profiles on the social networks. We need to improve the accuracy rate of the fake profile detection in the social networks. In this project we are proposing machine learning and natural language processing (NLP) techniques to improve the accuracy rate of the fake profiles detection in Instagram social media. We Implement the model support vector machine (SVM), Random forest classifier, Gradient boost classifier, Naïve bayes, and Logistic regression algorithm classification process.
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