Television Ratings: From Audimeter to Big Data
“Television Ratings: From Audimeter to Big Data” is a recuperative history of television ratings that examines audience measurement technologies and methods as precursory modes of cooperative data-driven consumer surveillance. First, I ague that audience measurement has been structured by its inherent reliance on the (inconsistent) cooperation—the co-optation as well as the collaboration—of viewers in the task of being measured. Modern surveillance theory tends to focus on how consumer surveillance becomes routinized or appropriated through resignation or alternatively, on the potential of counterveillance, but often overlooks the ways that participation in surveillance is often neither docile nor purposefully inimical, but still (whether it be out of ineptitude, boredom, or noncompliance) inconsistent. The surveillance complex constantly evolves in attempts to work around these forms of noncooperation. Rather than focusing on how cooperation is enacted, my use of cooperative surveillance focuses on how inconsistent cooperation shapes the very processes of surveillance. Second, I take the position that technology is political— it’s an important locus for the conflicts between corporate power and subject agency. In addition to analyzing the technologies that Nielsen and its competitors have used in their national panels, I use previously un-accessed archives to recuperate a history of experimental television ratings technologies and methods that are largely unknown. I argue that audience measurement technologies that failed or never came to fruition can tell us as much about the history of data regimes and consumer surveillance as mainstream ratings technologies. Further, these TV ratings experiments betray television culture’s embeddedness in problematic surveillance and also forecast the limitations of contemporary data regimes. The ratings industry’s response to the challenge of viewer cooperation has been a constant onslaught of technological experimentation to find the “proper standard” or “proper code” to create a commodifiable user/machine language.
My methodology combines top down industry analysis with ethnographic-inspired approaches by utilizing analysis of archival materials, interviews with industry professionals, trade discourse, technology patents, and legal documents, alongside interviews with former Nielsen panel participants. Ultimately, by pairing rigorous historical research with a contemporary media theory lens, my dissertation argues that the US commercial television system as a whole was founded on and even formative of these cooperative regimes of consumer surveillance, which continue to shape contemporary digital media culture.