Internal research by Netflix has revealed that the average user spends just 60 to 90 seconds browsing before they stop looking and do something else.
This surprisingly short window of time makes it more crucial than ever that the streaming company optimize their recommendations to entice users – something which has been made easier through their expansion from 60 to 190 countries last month.
Much has been made of Netflix’s recommendations algorithm, from how specific the categories can be to the erroneous titles it sometimes selects, and Computer Science applicants should consider the difficulties and benefits of adding global data to the recommendation pool. Similarly, HSPS and Archaeology and Anthropology students might be interested in how Netflix uses a film viewing differently in different countries – does an English man watching Love Actually engender the same recommendation as an Indian woman watching it? Should location or gender or age be a factor in determining what your movie preference says about your tastes?
Netflix appears to say ‘no’ to that question, as title suggestions are often made by finding other users who have watched similar titles and suggesting films those users have watched. Philosophy applicants should consider if this logic of disparate entities liking one object causally means they are more inclined to like another, similar object.
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