  Online media platforms have enabled users to connect with individuals,
organizations, and share their thoughts. Other than connectivity, these
platforms also serve multiple purposes - education, promotion, updates,
awareness, etc. Increasing the reputation of individuals in online media (aka
Social growth) 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 growth 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 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 being 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, description of the publicly available datasets and online tools,
and 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.
