Fake Account Detection on Social Media using Random Forest Classifier

As the growth of online social networks increases, everyone is associated and linked with social media. A massive amount of personal data is being attacked and stolen by cyber attackers. These fraudulent profiles also spread negative publicity, false news, and various malicious programs. One of the best ways is to detect these fake accounts, not only the best way but also it is the first step to stopping the negative news and false rumours. There are many efficient ways and techniques to detect these fake accounts. However, these techniques are based on or depend on the account features. The main aim of this research is to examine three machine learning algorithms i.e., random forest, logistic regression, and decision tree. The level of efficiency in the three mentioned methodologies are compared and the highest accuracy has been achieved for random forest classifier.