Big Questions for Social Media Big Data: Representativeness, Validity and Other Methodological Pitfalls

University of North Carolina at Chapel Hill

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Abstract

Large-scale databases of human activity in social media have captured scientific and policy attention, producing a flood of research and discussion. This paper considers methodological and conceptual challenges for this emergent field, with special attention to the validity and representativeness of social media big data analyses. Persistent issues include the over-emphasis of a single platform, Twitter, sampling biases arising from selection by hashtags, and vague and unrepresentative sampling frames. The socio-cultural complexity of user behavior aimed at algorithmic invisibility (such as subtweeting, mock-retweeting, use of “screen captures” for text, etc.) further complicate interpretation of big data…

Citation impact

706
total citations
FWCI
36.89
Percentile
100%
References
34
Citations per year

Authors

1

Topics & keywords

Keywords
  • Representativeness heuristic
  • Big data
  • Invisibility
  • Data science
  • Field (mathematics)
  • Social media
  • Computer science
  • Selection (genetic algorithm)
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