SPAM PROFILES DETECTION USING COMPUTATIONAL INTELLIGENCE METHODS ON ONLINE COMMUNITIES

Abstract

Online Social Networks (OSNs) are great environments for sharing ideas, following news, advertising products etc.,
and they have been widely used by many in the world. Although these are the advantages of social networks, it is
difficult to understand whether an account in social media platform such as Instagram, Twitter, Facebook really
belongs to a person or organization. Through creating fake and malicious accounts, unwanted content can spread over
the social network. Therefore, the prediction of fake accounts is an important problem. In this study, we applied
machine learning algorithms to this problem and we evaluated performances of different activation functions.
According to the experimental results, use of machine learning algorithms in detecting fake accounts yielded
successful results. The use of various activation functions in different layers on the ANN significantly affects the
results. In the literature, other classification methods have been widely used for detecting fake accounts and spammers
on online social Network. To the best of our knowledge, there is no brief study that classifies fake accounts using
ANNs with different activation functions.