Opinion Dynamics via Search Engines (and other Algorithmic Gatekeepers)

TL;DR

This paper models how search engine ranking algorithms influence opinion formation, revealing that popularity-based rankings can amplify misinformation and that personalization versus popularity affects information aggregation.

Contribution

It introduces a stylized model analyzing the impact of popularity and personalization in search rankings on opinion dynamics and misinformation spread.

Findings

Popularity-based rankings favor fewer websites, amplifying their traffic.

Personalization can hinder the aggregation of accurate information.

Popularity rankings can unintentionally promote misinformation.

Abstract

Ranking algorithms are the information gatekeepers of the Internet era. We develop a stylized model to study the effects of ranking algorithms on opinion dynamics. We consider a search engine that uses an algorithm based on popularity and on personalization. We find that popularity-based rankings generate an advantage of the fewer effect: fewer websites reporting a given signal attract relatively more traffic overall. This highlights a novel, ranking-driven channel that explains the diffusion of misinformation, as websites reporting incorrect information may attract an amplified amount of traffic precisely because they are few. Furthermore, when individuals provide sufficiently positive feedback to the ranking algorithm, popularity-based rankings tend to aggregate information while personalization acts in the opposite direction.