Taking Back and Giving Back: Redistributing Value in the Algorithmic Economy
Research on algorithmic imaginaries related to creators and influencers often focuses on their efforts to understand and best navigate algorithms to maximize visibility, and thus profits. However, there has been less work on how non-influencers work together to redistribute algorithmically-produced visibility through beliefs about how algorithms ought to work. Using "algorithmic ethnography" (Christin, 2020), Caplan and her co-authors, Elena Maris (UIC) and Hibby Thach (UIC) have identified three TikTok genres that they argue are emblematic of how practices of mutual aid (Spade, 2020) are unfolding over platforms. This article explores how these non-influencer communities demonstrate realizations of collective value and power within the economic system of TikTok, with an intent to disrupt and redirect the value in these systems (with sometimes real material consequences) as a form of political participation, compensation for cultural appropriation, or to provide relief and resources to those in need.
In addition to being a DLI Visiting Research Fellow, Robyn Caplan is a Researcher at Data & Society Research Institute and a founding member of the Platform Governance Research Network. She received her PhD from the School of Communication and Information at Rutgers University. She conducts research at the intersection of platform governance and media policy. Her research examines the impact of inter-and-intra-organizational behavior on platform governance and content moderation.
Caplan’s work has been published in journals such as Social Media + Society, First Monday, Big Data & Society, and Feminist Media Studies. Her work has been featured by publications like The Washington Post, The New York Times, Wired, NBC, and Al Jazeera. She has conducted research on a variety of issues regarding data-centric technological development on society, including government data policies, media manipulation, and the use of data in policing.