Preference Dynamics Under Personalized Recommendations
Sarah Dean, Jamie Morgenstern
Abstract
The design of content recommendation systems underpins many online platforms: social media feeds, online news aggregators, and audio/video hosting websites all choose how best to organize an enormous amount of content for users to consume. 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.
Topics & Concepts
Computer scienceDynamics (music)Media contentPreferenceMultimediaSocial mediaWorld Wide WebRecommender systemContent (measure theory)User-generated contentOnline videoInternet privacyMicroeconomicsPhysicsEconomicsMathematical analysisMathematicsAcousticsOpinion Dynamics and Social InfluenceConsumer Market Behavior and PricingRecommender Systems and Techniques