Fake View Analytics in Online Video Services
This addresses a critical issue for stakeholders like content owners and advertisers who rely on accurate view counts, but it appears incremental as it builds on existing detection methods without specifying major breakthroughs.
The paper tackled the problem of detecting fake views generated by bots in online video-on-demand services, showing that their developed algorithms are quite effective for this task.
Online video-on-demand(VoD) services invariably maintain a view count for each video they serve, and it has become an important currency for various stakeholders, from viewers, to content owners, advertizers, and the online service providers themselves. There is often significant financial incentive to use a robot (or a botnet) to artificially create fake views. How can we detect the fake views? Can we detect them (and stop them) using online algorithms as they occur? What is the extent of fake views with current VoD service providers? These are the questions we study in the paper. We develop some algorithms and show that they are quite effective for this problem.