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  1. Computational text analysis: Thoughts on the contingencies of an evolving method.Daniel Marciniak - 2016 - Big Data and Society 3 (2).
    Mapping a public discourse with the tools of computational text analysis comes with many contingencies in the areas of corpus curation, data processing and analysis, and visualisation. However, the complexity of algorithmic assemblies and the beauty of resulting images give the impression of ‘objectivity’. Instead of concealing uncertainties and artefacts in order to tell a coherent and all-encompassing story, retaining the variety of alternative assemblies may actually strengthen the method. By utilising the mobility of digital devices, we could create mutable (...)
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  • An invitation to critical social science of big data: from critical theory and critical research to omniresistance.Ulaş Başar Gezgin - 2020 - AI and Society 35 (1):187-195.
    How a social science of big data would look like? In this article, we exemplify such a social science through a number of cases. We start our discussion with the epistemic qualities of big data. We point out to the fact that contrary to the big data champions, big data is neither new nor a miracle without any error nor reliable and rigorous as assumed by its cheer leaders. Secondly, we identify three types of big data: natural big data, artificial (...)
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