A Survey on Machine Learning Algorithms for Detecting Fake Instagram Accounts
Karishma Anklesaria, Zeel Desai, Vikram Kulkarni, Harish Balasubramaniam · 2021 3rd International Conference on Advances in Computing, Communication Control and Networking (ICAC3N) · 2021
With the tremendous increase in internet usage since its inception, cybercrime and online scamming has become extremely abundant. This surge in online scams is only helped by the presence of social media, which serves as one of the most popular platforms for the scammers to target their victims. Social media platforms such as Instagram, Facebook, Whatsapp, Twitter, have become the primary hub for scamsters, and these platforms facilitate their dangerous activities. The fraudsters carry out such scams using fake accounts which help them hide their true identity. To prevent such scams, we need a tool that helps us differentiate between fake and legitimate profiles. The machine learning models like Artificial neural network, AdaBoost, Multi-Layer Perceptron, Random Forest and Stochastic Gradient Descent (SGD) were implemented and their performance was compared in this paper to differentiate between the fake and legitimate profiles. We compare the results of these algorithms using various parameters and find Random Forest to be the most efficient.