The persistent dominance of Facebook has led many scholars and policymakers to generate proposals to invigorate competition in social networking. In this piece we address a remedy that has received renewed attention: interoperability. Prior proposals of interoperability have focused on eroding entry barriers that exist due to user-based network effects. We focus here on data-generated network effects: the more data Facebook acquires from its users, the more its AI algorithms can learn and improve the content Facebook provides its users. Without access to a rich stream of user data, a social network is merely a static interface, with limited capacity to serve engaging or personalized content. As such, we propose a version of interoperability that addresses both user and data-driven network effects. In doing so, we also explicitly tackle the privacy issues that invariably arise whenever data is shared across firms.

By Cristian Santesteban & Shayne Longpre1

I. INTRODUCTION

The persistent dominance of the largest digital platforms has led many scholars and policymakers to generate proposals to invigorate competition in these markets.2 These proposals have ranged from splitting up firms, to stepping up antitrust enforcement, to imposing regulations on the sharing of data. In this piece, we address a remedy that has recently received renewed attention: interoperability for social media platforms.3 Interoperability has the potential to open up markets in the digital se

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