Do Online Video Recommendation Algorithms Increase Polarization? ...

Do personalization algorithms serve up ever more extreme videos to users, resulting in affective and issue polarization? Based in part on vivid anecdotes, a media narrative has taken hold ascribing worrisome power to hidden algorithms. Academic researchers have struggled to add evidence to this debate due to both data limitations and serious research design challenges. We propose a novel experimental approach that seeks to resolve the impasse on this critical question by randomizing the recommendations themselves. Using a custom-built interface that serves sequences of videos from YouTube's API, we create our own variations on the existing recommendation algorithm by manipulating the ideological balance of recommended video content to randomly assigned groups of subjects. This approach enables an attractive combination of experimental control and external validity without the need for reverse-engineering YouTube's blackbox recommendations. Subjects in our study will choose to watch a sequence of short videos ...