The Data Economy and Polarization on Social Media

Abstract

This paper studies the incentive of a social media platform (SMP) to increase polarization of its user network. I propose a two-group network model where the SMP earns revenue from user-data driven personalization. The objective of the SMP is to maximize the amount of valuable data generated. To this end, it relies on an algorithm that, at a cost, encourages users to form new links. Within a microfounded model, I show that two opposite forces impinge on the SMP. 1) The relative-size effect incentivizes the SMP to increase polarization since this increases amount of data it gathers. 2) The diversification effect incentivizes the SMP to decrease polarization since this increases value from data. Balancing these two forces, the SMP decides the optimal level of polarization it induces. Overall, the result provides a rationalization for opposite empirical results concerning the effect of an SMP on polarization. Further, if users prefer interacting with same-group users, the SMP internalizes this heterogeneity and has a greater incentive to increase polarization. Finally, increase in polarization can be tempered by levying a tax on the revenue of the SMP.