Taylor Arnold and Lauren Tilton
Distant Viewing TV (distanttv.org) applies computational methods to the study of fourteen series from the Network Era of American Television (1952-1985), utilizing and developing cutting-edge techniques in computer vision to analyze moving image culture on a large scale. Given that long-running television series broadcast hundreds of episodes, and the major networks run dozens of series each season, previous studies of network television have had to rely on a close analysis of a subset of series, episodes, and scenes (Baughman 1993; Dow 1996; Morely 2003; Spangler 2003). Distant Viewing TV builds off of this scholarship by applying computational approaches, specifically machine learning techniques, that can analyze the contents of tens of thousands of hours of television programming. Bringing a “distant reading” approach, or what we term “distant viewing,” to these programs sheds light on the formal rigor of these programs while making possible a comprehensive study of American television comedies over a thirty year span.
Specifically, Distant TV is making a scholarly intervention in how we study TV. The project focuses in on how visual space is used by characters, modeling a new mode of cultural analysis within TV studies. While there is a growing body of television scholarship in media studies, now known as TV studies, the leading scholarship in the field focuses on “prestige television,” a term used to describe TV that is designed to appeal to middle- and upper-class viewers, critics, and awards committees (Lotz 2014; Thompson and Mittell 2013; Wiliams 2014). The challenge with this increased attention to prestige television is that it reinforces a bias toward “cinematic” or “novelistic” television and deepens an ingrained view of Network Era comedy as formally simple, even simple-minded, without any artistry. While the study of prestige television’s high production values and experimental techniques makes the genre ideally suited to close reading, the repetitiousness and genre conventions of studio filming are best served by a distant viewing practice in which computational tools uncover the subtleties of form and the evolution of a program’s style over time. In this presentation, we will focus on our initial work of extracting relevant features from episodes of Bewitched (1964-1972).
Along with applying distant viewing techniques to our particular object of study, we are building the DTV Toolkit, a software library that automatically extracts metadata features from a corpus of moving images. Specifically, it determines the placement and identities of faces in every shot and the identity of the current scene location. It will be scalable to other genres of moving image culture. We will show the current version of this library and would be delighted to get feedback from the AV SIG on what they would like to see as a part of this toolkit.