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YouTube Algorithm Exposed: DMI Summer School project week 1

DATACTIVE participated in the first week of the Digital Methods Initiative summer school 2019 with a data sprint related to the side project ALEX. DATACTIVE’s insiders Davide and Jeroen, together with research associate and ALEX’s software developer Claudio Agosti, pitched a project aimed at exploring the logic of YouTube’s recommendation algorithm, using the ALEX-related browser extension youtube.tracking.exposed. ytTREX allows you to produce copies of the set of recommended videos, with the main purpose to investigate the logic of personalization and tracking behind the algorithm. During the week, together with a number of highly motivated students and researchers, we engaged in collective reflection, experiments and analysis, fueled by Brexit talks, Gangnam Style beats, and the secret life of octopuses. Our main findings (previewed below, and detailed later in a wiki report) pertain look into which factors (language settings, browsing behavior, previous views, domain of videos, etc.) help trigger the highest level of personalization in the recommended results.

 

Algorithm exposed_ investigasting Youtube – slides