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This paper contributes to the ongoing discussions on the scholarly access tosocial media data, discussing a case where this access is barred despite itsvalue for understanding and countering online disinformation and despite theabsence of privacy or copyright issues. Our study concerns YouTube's engagementmetrics and, more specifically, the way in which the platform removes "fakeviews" (i.e., views considered as artificial or illegitimate by the platform).Working with one and a half year of data extracted from a thousand FrenchYouTube channels, we show the massive extent of this phenomenon, which concernsthe large majority of the channels and more than half the videos in our corpus.Our analysis indicates that most fakes news are corrected relatively late inthe life of the videos and that the final view counts of the videos are notindependent from the fake views they received. We discuss the potential harmthat delays in corrections could produce in content diffusion: by inflatingviews counts, illegitimate views could make a video appear more popular than itis and unwarrantedly encourage its human and algorithmic recommendation.Unfortunately, we cannot offer a definitive assessment of this phenomenon,because YouTube provides no information on fake views in its API or interface.This paper is, therefore, also a call for greater transparency by YouTube andother online platforms about information that can have crucial implications forthe quality of online public debate.

Doing data science with platforms crumbs: an investigation into fakes views on YouTube