Publication | Closed Access
On fairness
50
Citations
19
References
2015
Year
Social Data AnalysisComputational Social ScienceSocial Media UsersSocial NetworksSocial MediaEngineeringSocial ComputingSociologyData PrivacySocial Aspects Of Data MiningSocial Data ManagementRacismArtsContent AnalysisSocial Medium DataPrivacy ConcernSocial Media MiningJournalism
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.
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