Algorithmic Audiencing: Why we need to rethink free speech on social media

Abstract

Social media platforms, such as Facebook, are today’s agoras, the spaces where public discourse takes place. Freedom of speech on social media has thus become a matter of concern, with calls for better regulation. Public debate revolves around content moderation, seen by some as necessary to remove harmful content, yet as censorship by others. In this paper we argue that the current debate is exclusively focused on the speaking side of speech but overlooks an important way in which platforms have come to interfere with free speech on the audience side. Rather than simply speaking to one’s follower network, algorithms now organise speech on social media with the aim to increase user engagement and marketability for targeted advertising. The result is that audiences for speech are now decided algorithmically, a phenomenon we term ‘algorithmic audiencing’. We put forward algorithmic audiencing as a discovery, a novel phenomenon that has been overlooked so far. We show that it interferes with free speech in unprecedented ways not possible in pre-digital times, by amplifying or suppressing speech for economic gain, which in turn distorts the free and fair exchange of ideas in public discourse. When black-boxed algorithms determine who we speak to the problematic for free speech changes from ‘what can be said’ to ‘what will be heard’ and ‘by whom’. We must urgently problematize the audience side of speech if we want to truly understand, and regulate, free speech on social media. For IS research, algorithmic audiencing opens up entirely new research avenues.