Feed for Good? On the effects of personalized algorithms in social media

Theory-Experimental Seminar

Miguel Risco

University of Bonn

20-Nov-2023

seminar – 14:30

Social media platforms govern the exchange of information among users with preferences for sincerity and conformity by providing personalized feeds. This paper shows that the pursuit of engagement maximization results in low-quality communication and the proliferation of echo chambers. A monopolistic platform disregards social learning and curates feeds that primarily consist of content from like-minded individuals. We study the consequences on learning and welfare resulting from transitioning to this algorithm from the previously employed chronological feed. We show that the platform could create value by using its privileged information to design algorithms that balance learning and engagement, maximizing users’ welfare. However, incentivizing a monopolist to embrace such an approach presents challenges. To address this, we discuss interoperability as a possible regulatory solution to overcome network effects in platform competition, level the playing field, and prompt platforms to adopt the socially optimal algorithm.