Papers
Topics
Authors
Recent
Search
2000 character limit reached

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

Published 29 Mar 2021 in cs.SI | (2103.15250v1)

Abstract: 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.

Citations (5)

Summary

No one has generated a summary of this paper yet.

Paper to Video (Beta)

No one has generated a video about this paper yet.

Whiteboard

No one has generated a whiteboard explanation for this paper yet.

Open Problems

We haven't generated a list of open problems mentioned in this paper yet.

Continue Learning

We haven't generated follow-up questions for this paper yet.

Collections

Sign up for free to add this paper to one or more collections.