Reading List

Platform Studies

Plantin, J.-C., C. Lagoze, P. N. Edwards, and C. Sandvig. “Infrastructure Studies Meet Platform Studies in the Age of Google and Facebook.” New Media & Society, 2016.

Bogost, I., & Montfort, N. (2009). Platform studies: Frequently questioned answers.

Gillespie, Tarleton. “The Politics of ‘Platforms.’” New Media & Society 12, no. 3 (2010): 347–364.

Blok, A., Marquet, C., Courmont, A., Minor, K., Young, M., Hoyng, R., & Nold, C. (2017). Data Platforms and Cities. Tecnoscienza. Italian Journal of Science & Technology Studies.

Critical Data Studies

Thatcher, J., O’Sullivan, D., & Mahmoudi, D. (2016). Data colonialism through accumulation by dispossession: New metaphors for daily data. Environment and Planning D: Society and Space, 34(6), 990-1006.

Dalton, Craig M., Linnet Taylor, and Jim Thatcher (alphabetical). “Critical Data Studies: A Dialog on Data and Space.” Big Data & Society 3, no. 1 (January 5, 2016): 2053951716648346.

Iliadis, Andrew, and Federica Russo. “Critical Data Studies: An Introduction.” Big Data & Society 3, no. 2 (December 1, 2016): 2053951716674238.

Kitchin, R. (2017). Thinking critically about and researching algorithms. Information, Communication & Society, 20(1), 14-29.

Critical Infrastructure Studies

Anand, N. (2015). Leaky states: Water audits, ignorance, and the politics of infrastructure. Public Culture, 27(2 (76)), 305-330. [Link]

An MLA Session on Critical Infrastructure Studies [Link]


Browne, S. (2015). Dark matters: On the surveillance of blackness. Duke University Press. [Link]

Marx, G. T. (2016). Windows into the soul: Surveillance and society in an age of high technology. University of Chicago Press. [Link]

Brayne, S. (2017). Big data surveillance: The case of policing. American Sociological Review82(5), 977-1008. [Link]

Haggerty, Kevin D., and Richard V. Ericson. “The Surveillant Assemblage.” The British Journal of Sociology 51, no. 4 (December 1, 2000): 605–22.

 Algorithmic Opacity

Seaver, N. (2017). Algorithms as culture: Some tactics for the ethnography of algorithmic systems. Big Data & Society4(2), 2053951717738104. [Link]

Gillespie, T. (2014). The relevance of algorithms. Media technologies: Essays on communication, materiality, and society, 167.

Burrell, J. (2016). How the machine ‘thinks’: Understanding opacity in machine learning algorithms. Big Data & Society, 3(1), 2053951715622512.

Diakopoulos, N. (2015). Algorithmic accountability: Journalistic investigation of computational power structures. Digital Journalism, 3(3), 398-415.

Ziewitz, M. (2016). Governing algorithms: Myth, mess, and methods. Science, Technology, & Human Values, 41(1), 3-16.

Kroll, J. A., Barocas, S., Felten, E. W., Reidenberg, J. R., Robinson, D. G., & Yu, H. (2016). Accountable algorithms. U. Pa. L. Rev., 165, 633.

Ananny, M., & Crawford, K. (2016). Seeing without knowing: Limitations of the transparency ideal and its application to algorithmic accountability. new media & society, 1461444816676645.

Fairness and Bias

Eubanks, V. (2018). Automating inequality: How high-tech tools profile, police, and punish the poor. [Link]

Barocas, S., & Selbst, A. D. (2016). Big data’s disparate impact. Cal. L. Rev., 104, 671.

O’Neil, C. (2016). Weapons of math destruction: How big data increases inequality and threatens democracy. Broadway Books.

Ananny, M. (2016). Toward an ethics of algorithms: Convening, observation, probability, and timeliness. Science, Technology, & Human Values, 41(1), 93-117.


Recent news articles can be found on the CritPlat Reddit [Link]