Crowding out the truth? A simple model of misinformation, polarization and meaningful social interactions

10/05/2022

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by   Fabrizio Germano, et al.

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This paper provides a simple theoretical framework to evaluate the effect of key parameters of ranking algorithms, namely popularity and personalization parameters, on measures of platform engagement, misinformation and polarization. The results show that an increase in the weight assigned to online social interactions (e.g., likes and shares) and to personalized content may increase engagement on the social media platform, while at the same time increasing misinformation and/or polarization. By exploiting Facebook's 2018 "Meaningful Social Interactions" algorithmic ranking update, we also provide direct empirical support for some of the main predictions of the model.