Switch to: References

Add citations

You must login to add citations.
  1. The optical unconscious of Big Data: Datafication of vision and care for unknown futures.Daniela Agostinho - 2019 - Big Data and Society 6 (1).
    Ever since Big Data became a mot du jour across social fields, optical metaphors such as the microscope began to surface in popular discourse to describe and qualify its epistemological impact. While the persistence of optics seems to be at odds with the datafication of vision, this article suggests that the optical metaphor offers an opportunity to reflect about the material consequences of the modes of seeing and knowing that currently shape datafied worlds. Drawing on feminist new materialism, the article (...)
    Download  
     
    Export citation  
     
    Bookmark  
  • Data out of place: Toxic traces and the politics of recycling.Nanna Bonde Thylstrup - 2019 - Big Data and Society 6 (2).
    It has become increasingly common to talk about “digital traces”. The idea that we leak, drop and leave traces wherever we go has given rise to a culture of traceability, and this culture of traceability, I argue, is intimately entangled with a socio-economics of data disposability and recycling. While the culture of traceability has often been theorised in terms of, and in relation to, privacy, I offer another approach, framing digital traces instead as a question of waste. This perspective, I (...)
    Download  
     
    Export citation  
     
    Bookmark   4 citations  
  • “Reach the right people”: The politics of “interests” in Facebook’s classification system for ad targeting.Kjerstin Thorson, Chankyung Pak, Mel Medeiros & Kelley Cotter - 2021 - Big Data and Society 8 (1).
    Political campaigns increasingly rely on Facebook for reaching their constituents, particularly through ad targeting. Facebook’s business model is premised on a promise to connect advertisers with the “right” users: those likely to click, download, engage, purchase. The company pursues this promise by algorithmically inferring users’ interests from their data and providing advertisers with a means of targeting users by their inferred interests. In this study, we explore for whom this interest classification system works in order to build on conversations in (...)
    Download  
     
    Export citation  
     
    Bookmark