Abstract
Kennedy maps out key criticisms of contemporary data mining in order to consider whether these apply to ordinary data mining in subsequent chapters. She organises criticisms of social media and other data mining into four categories: (1) it results in less privacy and more surveillance; (2) it is mobilised for the purposes of discrimination and control; (3) access to it is unequal and this results in inequality; and (4) it is methodologically troubling, because the data it generates shape the social world in opaque ways. She argues that the focus on structures of datafication evident in these criticisms means that the possibility of acting with agency in the face of data power has rarely been considered. Thinking about agency is one way of addressing the question of whether it is possible to do data mining in ways that makes a positive contribution to society, so she highlights ways of doing this in relation to data mining in the second half of the chapter.
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Notes
- 1.
- 2.
Some argue that Zuckerberg did this in order to justify his company’s controversial decision to change the default privacy settings of its users’ accounts and make them more public than they had previously been.
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Christian Fuchs is another writer who has highlighted how the discriminatory potential of data mining is captured in the interests of capital (for example, Fuchs 2011).
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The social analytics approach was first developed by Couldry and collaborators on the Storycircle project, to study how organisations use analytics to meet their goals. See http://storycircle.co.uk/.
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Kennedy, H. (2016). What Should Concern Us About Social Media Data Mining? Key Debates. In: Post, Mine, Repeat. Palgrave Macmillan, London. https://doi.org/10.1057/978-1-137-35398-6_3
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