Preference Dynamics Under Personalized Recommendations. (arXiv:2205.13026v1 [cs.LG])

Many projects (both practical and academic) have designed algorithms to match
users to content they will enjoy under the assumption that user's preferences
and opinions do not change with the content they see. Evidence suggests that
individuals' preferences are directly shaped by what content they see --
radicalization, rabbit holes, polarization, and boredom are all example
phenomena of preferences affected by content. Polarization in particular can
occur even in ecosystems with "mass media," where no personalization takes
place, as recently …

arxiv dynamics personalized personalized recommendations recommendations