Big data audiences: Critical approaches to the datafication of audience ontologies in contemporary media industries

Abstract

The current transformations in how audiences are datafied, including how that data is then traded and sold, used in various algorithms and AI models, and executed on to shape our media ecosystems, necessitate renewed frameworks for conceptualizing these datafied audience ontologies, which we refer to in this issue as ‘big data audiences’. Big data audiences are the lifeblood of the contemporary digital media ecosystem, with significant epistemic and cultural consequences that social scientists and humanists have not sufficiently grappled with. While political economy remains central to understanding the contemporary contexts of audience datafication, this issue demonstrates how theories and methods from the domains of social and humanistic research are equally essential for conceptualizing big data audiences. The issue brings together a range of methodological approaches and aims to catalyze critical media scholarship on audiences that explores the industrial and cultural aspects of datafied audience ontologies in media industries big and small across the globe.