Data craft: a theory/methods package for critical internet studies

ABSTRACT

Disinformation campaigns continue to thrive online, despite social media companies’ efforts at identifying and culling manipulation on their platforms. Framing these manipulation tactics as ‘coordinated inauthentic behavior,’ major platforms have banned culprits and deleted the evidence of their actions from social activity streams, making independent assessment and auditing impossible. While researchers, journalists, and civil society groups use multiple methods for discovering and tracking disinformation, platforms began to publish highly curated data archives of disinformation in 2016. When platform companies reframe manipulation campaigns, however, they downplay the importance of their products in spreading disinformation. We propose to treat social media metadata as a boundary object that supports research across platforms and use metadata as an entry point for investigating manipulation campaigns.

We illustrate how platform companies’ responses to disinformation campaigns are at odds with the interests of researchers, civil society, policy-makers, and journalists, limiting the capacity to audit the role that platforms play in political discourse. To show how platforms’ data archives of ‘coordinated inauthentic behavior’ prevent researchers from examining the contexts of manipulation, we present two case studies of disinformation campaigns related to the Black Lives Matter Movement. We demonstrate how data craft – the exploitation of metrics, metadata, and recommendation engines – played a prominent role attracting audiences to these disinformation campaigns. Additionally, we offer some investigative techniques for researchers to employ data craft in their own research of the disinformation. We conclude by proposing new avenues for research for the field of Critical Internet Studies.

KEYWORDS:

• Data craft
• disinformation
• metadata
• platforms
• social movements

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Correction

Correction Statement

This article was originally published with errors, which have now been corrected in the online version. Please see Correction (https://doi.org/10.1080/1369118X.2019.1655230)

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes on contributors

Amelia Acker is an assistant professor in the School of Information at the University of Texas at Austin. She is an information scientist who researchers data literacy, metadata, and information infrastructures that support long-term cultural memory.

Joan Donovan is the Director of the Technology and Social Change Research Project at the Shorenstein Center on Media, Politics and Public Policy at Harvard Kennedy School, where she researches media manipulation, disinformation, and adversarial media movements.

Notes

1. APIs or Application Programming Interfaces are software that specify rules for access and extraction of data. APIs allow third parties such as data brokers, app developers, advertizers, journalists and scholarly researchers access to social media data extracted from platforms.