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Fake Rating Analysis from the Movie Dataset: Using Supervised Techniques

Abstract: A social networking site provides a platform for different users to interact with. This forum attracts not only people but also business owners by selling products. The most commonly used social media platform is to promote online films. For this purpose, fake profiles are created by developers. Finding such a false profile to reveal actual movie ratings is the main objective of this study. For fake profile categories such as pre-processing, classification and classification are followed. In pre-processing, sound or other impurities are removed from the movie database if it contains. The next step is to classify the features and select the functional features based on the analytical analysis. Separation uses a Raphson-based repetitive model in testing a fake profile. The findings of the proposed method are presented in terms of F-Score, category accuracy, sensitivity and clarity. The overall result is an improvement in important genes. Keywords: Fake Rating, Supervised Techniques, F-score, Classification Accuracy