engleski

Spammer Detection Approaches in Online Social Network (OSNs): A Survey

In recent years, spammer has imbued every social network platform. The growth in users in social platforms like Instagram, Facebook, Sina Weibo, Twitter, YouTube, etc. has unfolded new approaches for spammers. To get the financial benefit, spammers exploit social network platforms using flooded content shared by the users. In order to protect user information and accounts from spammers, many researchers have proposed defensive mechanisms and detection methods. Over the last few years, researchers develop many spam detection methods which improve the performance of user’s account. Therefore, we are motivated to point out few surveys about various methods by which the spammer can spread and some detection mechanisms to protect users and their account information. The solution for the detection of a spammer is different based on the collected dataset and predictive user analysis. This survey includes (1) Various detection mechanisms including the way of spreading spam. (2) Analysis of user contents based on their account information and posts including a comparative analysis of various methodologies for the detection of spammers. (3) Open issues and challenges in social network spam detection techniques.

Security ; Online Social Networks ; Cloud Computing

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