Isomorphism through algorithms: Institutional dependencies in the case of Facebook
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2018-01
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<jats:p> Algorithms and data-driven technologies are increasingly being embraced by a variety of different sectors and institutions. This paper examines how algorithms and data-driven technologies, enacted by an organization like Facebook, can induce similarity across an industry. Using theories from organizational sociology and neoinstitutionalism, this paper traces the bureaucratic roots of Big Data and algorithms to examine the institutional dependencies that emerge and are mediated through data-driven and algorithmic logics. This type of analysis sheds light on how organizational contexts are embedded into algorithms, which can then become embedded within other organizational and individual practices. By investigating technical practices as organizational and bureaucratic, discussions about accountability and decision-making can be reframed. </jats:p>
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Caplan, Robyn, and danah boyd (2018). Isomorphism through algorithms: Institutional dependencies in the case of Facebook. Big Data & Society, 5(1). pp. 205395171875725–205395171875725. 10.1177/2053951718757253 Retrieved from https://hdl.handle.net/10161/29029.
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Robyn Caplan
Robyn Caplan is an Assistant Professor at Duke University's Sanford School of Public Policy, and a Senior Lecturing Fellow in the Center for Science & Society at Duke University. She is also a Researcher Affiliate at Data & Society Research Institute, where she worked as a Senior Researcher, an Affiliate at the Center for Information Technology and Policy at UNC-Chapel Hill, 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. Her most recent work examines the history of the verified badge (the blue checkmark) at platforms.
Caplan’s work has been published in journals such as the International Journal of Communications, 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.
Unless otherwise indicated, scholarly articles published by Duke faculty members are made available here with a CC-BY-NC (Creative Commons Attribution Non-Commercial) license, as enabled by the Duke Open Access Policy. If you wish to use the materials in ways not already permitted under CC-BY-NC, please consult the copyright owner. Other materials are made available here through the author’s grant of a non-exclusive license to make their work openly accessible.