Detection of Fake Twitter Accounts with Machine Learning Algorithms

Abstract

Today, social networks have been part of many people's lives. Many activities such as communication, promotion, advertisement, news, agenda creation have started to be done through social networks. Some malicious accounts on Twitter are used for purposes such as misinformation and agenda creation. This is one of the basic problems in social networks. Therefore, detection of malicious account is significant. In this study, machine learning-based methods were used to detect fake accounts that could mislead people. For this purpose, the dataset generated was pre-processed and fake accounts were determined by machine learning algorithms. Decision trees, logistic regression and support vector machines algorithms are used for the detection of fake accounts. Classification performances of these methods are compared and the logistic regression proved to be more successful than the others.