Performance Analysis of Machine Learning Algorithms in SMP: A Case Study of Twitter

Abstract

The number of people using Social Media Platform (SMP) is increasing day by day. A few users may hide their identity with malicious intentions. Previous research has detected fake accounts created by bots using machine learning concepts. These ML concepts used engineered features such as the ‘following-to-followers ratio’ which is generally available in their accounts. In previous studies these similarly clustered features were applied to the machine learning models for detection of fake and real accounts. In the recent research the behavioural features like the sentient of the tweet posted on twitter is considered along with the parameters. Here, the ML models are also trained to use engineered features depending on behavioural data.