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Thursday, October 11 • 4:00pm - 5:30pm
Assemblages of the Socio-Technical I

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Ngai Keung Chan
User-generated rating systems are a ubiquitous mechanism for prodding users to perform “data labor” to monitor and evaluate other users’ performance in platform economies. Much of the research has shown that how these systems can exercise control over workers through the automated algorithmic labor management. For rating systems to operate, it requires social coordination between human and non-human actors to legitimize these systems. Drawing on the concept of boundary object, this study uses Uber’s rating system as a case study to examine the practical politics of user-generated rating systems. In particular, it aims to critically assess (1) who can participate in constructing Uber’s rating system as a boundary object; (2) how the rating system creates standardized and residual categories, and for what purposes, and (3) how different actors ascribe multiple meanings to the rating system. Using a loosely defined standard of quantifying drivers’ performance, Uber’s rating system provides fertile ground for the Federal Trade Commission, Uber, and drivers to coordinate their information and work needs without sharing a consensus on their identities and practices. The rating system serves both as a means to build trust among drivers and riders in an anonymous market and as a rhetorical justification for Uber to decide who can continue working on the platform. Therefore, this article argues that the rating syst
em becomes a socio-technical mechanism of governance that constructs drivers as “calculative publics” in the platform economy.

Justin Grandinetti, Charles Ecenbarget
The 2017 partnership between the National Football League (NFL) and Amazon Web Services (AWS) promises novel forms of cutting-edge real-time statistical analysis by utilizing both radio frequency identification (RFID) chips and Amazon’s cloud-based machine learning and data-analytics tools. This use of RFID is heralded for its possibilities: for broadcasters, now capable of providing more thorough analysis; for fans, who can experience the game on a deeper analytical level using the NFL’s Next Gen Stats; and for coaches, who can capitalize on data-driven pattern recognition to gain a statistical edge over their competitors in real-time. The synthesis of RFID and cloud computing data-analytic infrastructure via the NFL/AWS partnership also raises new questions about the use of mobile technologies, the normalization of tracking and big data through entertainment, and the desire for data-driven ways of overcoming the limitations of human perception.

We apply this case study to examine the related issues of RFID and big data analytics as material mobile media implicated in the production of space and new data-driven perception and cognition. Additionally, the promotion of RFID via the NFL’s popularity functions as part of discursive strategies that normalize RFID infrastructures of tracking and surveillance. In adding to literature on RFID as mobile technology, we expand upon recent scholarship focused on RFID and the production of space, big data and cognition, and discursive positionings. Consequently, we position the novel developments and implications of RFID technology as part of material infrastructures with pervasive impacts on the construction of space, perception, and cognition.

Priya Kumar, Sarita Schoenebeck, Jessica Vitak
The blurry, grayscale, wedge-shaped ultrasound image is largely undecipherable as a medical object but instantly recognizable as a social and cultural marker of pregnancy. When shared online, the image becomes one way that expectant parents enact their emerging identities. But how does sharing this image within networked publics such as social network sites or online communities enact the fetus? We explore this question through a qualitative analysis of ultrasound images shared on the online community BabyCenter.

Sonographers use the ultrasound image to document fetal life and check for abnormalities; pregnant women perceive the image as a depiction of their baby and a way of connecting to it. Ultrasound is thus what anthropologist Janelle Taylor calls a “hybrid practice” that serves diagnostic and entertainment purposes. It produces the fetus as a patient while also showing the fetus as a baby for the pregnant woman to see. Prior work has observed that this practice of “showing the fetus” also emerges in keepsake ultrasound business, which are commercial, non-medical sites. This study, which analyzes a sample of posts from the largest ultrasound-focused message board on BabyCenter, examines what type of ultrasound images are shared online and how users make sense of them. It offers a window into how expectant parents negotiate the fetus in a social setting online, extending research on ultrasound into networked publics. The findings inform scholarly understanding of the enactment of parenthood online as well as the construction of future children online.

Carlos Frederico de Brito d'Andréa, André Goes Mintz
Considering the importance of cross-platform circulation of web contents for digital methods-oriented research, in this study we aim to expand the types of digital objects used as ‘traffic tags’ by focusing on static images as traces of online associations. We pursue this goal through a methodological experiment with Google Cloud Vision API, a computing framework for visual content analysis. Its Web Detection module pairs typical computer vision operations with Google’s search mechanism, partly performing as a more specialized batch reverse image search engine. This feature thus allows to potentially retrieve images’ spread across the web. We discuss the implications of this non-verbal methodological approach by tracking the 'live' cross-platform circulation of images shared on Twitter in the context of 2018 FIFA World Cup Final Draw ceremony, held on December 2017. Following a novel methodological protocol, we ran several iterations of Vision API processing, thus generating a time series of URLs pointing to pages in which images matching the ones being processed were found. The study analyses in depth the circulation of four popular images about the broadcasted media event, observing their ‘live’ spreading dynamics as well as the computer vision API performance. Among the findings, we point out the adoption of images as 'traffic tags' for cross-platform analysis as a promising approach to study web circulation beyond language barriers and mainstream platforms. Also, we find relevant data to discuss the specificities of the API’s algorithms and its opacity as inherent issues of the digital methods approach.

Thursday October 11, 2018 4:00pm - 5:30pm EDT
Sheraton - Salon 5