Video and textual tutorial, on the basic usage, the evidence page, and everything a researcher need to start analyzing YT!
A collective observation of the Youtube personalization algorithm; addressing COVID-19 and getting evidence on how recommendations works
Coordinated collection of yt search results; to spot tendencies, bubbles, and biases. real time psedonymized open data feed.
Collective project made during the Digital Methods Winter School 2021. This paper studies the construction of filter bubbles and political polarization under YouTube 's algorithmic personalization, in a time where the political division runs deep in the US and the 2020 election reaffirms the polarization.
Three days analysis with ten researchers. The research aim to split the group in two and see how different activities are considered by YT to personalize the next recommendation.
Three days initial research with a dozen of students: we began by mapping Youtube personalization differences and distances.