ABOME: A Multi-platform Data Repository of Artificially Boosted Online Media Entities

Hridoy Sankar Dutta, Udit Arora, Tanmoy Chakraborty

The rise of online media has incentivized users to adopt various unethical and artificial ways of gaining social growth to boost their credibility within a short time period. In this paper, we introduce ABOME, a novel multi-platform data repository consisting of artificially boosted (also known as blackmarket-driven collusive entities) online media entities such as Twitter tweets/users and YouTube videos/channels, which are prevalent but often unnoticed in online media. ABOME allows quick querying of collusive entities across platforms. These include details of collusive entities involved in blackmarket services to gain artificially boosted appraisals in the form of likes, retweets, views, comments, follows and subscriptions. ABOME contains data related to tweets and users on Twitter, YouTube videos and YouTube channels. We believe that ABOME is a unique data repository that can be used as a benchmark to identify and analyze blackmarket-driven fraudulent activities in online media. We also develop SearchBM, an API and a web portal that offers a free service to identify blackmarket entities.

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