The methodology Guillaume Chaslot used to detect videos YouTube was recommending during the election – and how the Guardian analysed the data
YouTube’s recommendation system draws on techniques in machine learning to decide which videos are auto-played or appear “up next”. The precise formula it uses, however, is kept secret. Aggregate data revealing which YouTube videos are heavily promoted by the algorithm, or how how many views individual videos receive from “up next” suggestions, is also withheld from the public.
Disclosing that data would enable academic institutions, fact-checkers and regulators (as well as journalists) to assess the type of content YouTube is most likely to promote. By keeping the algorithm and its results under wraps, YouTube ensures that any patterns that indicate unintended biases or distortions associated with its algorithm are concealed from public view.