Knowing the Audience in the Information Age: Big Data and Social Media in the US Television Industry

Abstract

In the American television industry, knowledge about the audience is a structuring factor that essentially all operations are organized around. For the majority of American television’s history, the Nielsen ratings—which offered insights into viewership numbers and demographics using principles of inferential statistics—were the dominant audience information regime that determined everything from the viability of creative projects to relations between advertisers and networks. In the digital age, however, thanks to social media and big data technologies, the volume, velocity, and dimensionality of the audience information available to this industry has increased exponentially and at a rapid pace. Although little about how to use them is fully settled, these new forms of advanced audience information have been transformative in industry operations. This dissertation explores and interrogates the ways these new forms of audience information are reshaping practices and expectations across a range of industry sectors, along the way altering industry professionals’ perceptions of their jobs and identities, shifting economic arrangements and partnerships, and requiring new categories of labor to manage the incoming information.

Based on industry fieldwork and interviews conducted in 2017 alongside a longer-ranging analysis of trade press (2010-2018), the project takes a deep dive into different industry sectors—business operations, creative production, and social media promotion/engagement—to show how each sector is reconfiguring itself in light of the new types audience information available to it. With so much information and multiple technological paths to reaching it, each sector and firm is free to construct the audience in the way that best serves their interests, a move that has destabilized industrial common sense around notions of audience, and which makes sense in the context of an algorithmic culture with an orientation towards personalization. In offering an empirical account of people's experiences dealing with these technologies in this field of cultural production, it also demonstrates that the mixture of "algorithms" and "culture" is not a top down process of imposing rationalization and datafication, but one where humans have agency and must find ways to make algorithmic technologies fit into existing cultural milieus. Although much about how to use advanced audience information is still evolving, the processes of making sense of it documented here show how a major “legacy” commercial media industry is navigating the transformations of contemporary algorithmic culture.