Blackmarket-Driven Collusion on Online Media: A Survey
ACM/IMS Transactions on Data Science
Online media platforms have enabled users to connect with individuals and organizations, and share their thoughts. Other than connectivity, these platforms also serve multiple purposes, such as education, promotion, updates, and awareness. Increasing, the reputation of individuals in online media (aka social reputation ) is thus essential these days, particularly for business owners and event managers who are looking to improve their publicity and sales. The natural way of gaining social
... ion is a tedious task, which leads to the creation of unfair ways to boost the reputation of individuals artificially. Several online blackmarket services have developed a thriving ecosystem with lucrative offers to attract content promoters for publicizing their content online. These services are operated in such a way that most of their inorganic activities are going unnoticed by the media authorities, and the customers of the blackmarket services are less likely to be spotted. We refer to such unfair ways of bolstering social reputation in online media as collusion . This survey is the first attempt to provide readers a comprehensive outline of the latest studies dealing with the identification and analysis of blackmarket-driven collusion in online media. We present a broad overview of the problem, definitions of the related problems and concepts, the taxonomy of the proposed approaches, and a description of the publicly available datasets and online tools, and we discuss the outstanding issues. We believe that collusive entity detection is a newly emerging topic in anomaly detection and cyber-security research in general, and the current survey will provide readers with an easy-to-access and comprehensive list of methods, tools, and resources proposed so far for detecting and analyzing collusive entities on online media.