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On fairness: User perspectives on social media data mining

Research output: Indexed journal article Articlepeer-review

44 Citations (Scopus)

Abstract

What do social media users think about social media data mining? To date, this question has been researched through quantitative studies that produce diverse findings and qualitative studies adopting either a privacy or a surveillance perspective. In this article, we argue that qualitative research which moves beyond these dominant paradigms can contribute to answering this question, and we demonstrate this by reporting on focus group research in three European countries (the United Kingdom, Norway and Spain). Our method created a space in which to make sense of the diverse findings of quantitative studies, which relate to individual differences (such as extent of social media use or awareness of social media data mining) and differences in social media data mining practices themselves (such as the type of data gathered, the purpose for which data are mined and whether transparent information about data mining is available). Moving beyond privacy and surveillance made it possible to identify a concern for fairness as a common trope among users, which informed their varying viewpoints on distinct data mining practices. We argue that this concern for fairness can be understood as contextual integrity in practice (Nissenbaum, 2009) and as part of broader concerns about well-being and social justice.
Original languageEnglish
Pages (from-to)270-288
Number of pages19
JournalConvergence-the International Journal of Research Into New Media Technologies
Volume23
Issue number3
DOIs
Publication statusPublished - Jun 2017
Externally publishedYes

Keywords

  • Contextual integrity
  • Digital data
  • Fairness
  • Privacy
  • Social justice
  • Social media data mining
  • Surveillance
  • User perspectives
  • Well-being

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