Statistical Genre Analysis: Toward Big Data Methodologies in Technical Communication

S. Scott Graham University of Wisconsin–Milwaukee ; Sang-Yeon Kim ; Danielle M. DeVasto ; William Keith University of Wisconsin–Milwaukee

Abstract

This article pilots a study in statistical genre analysis, a mixed-method approach for (a) identifying conventional responses as a statistical distribution within a big data set and (b) assessing which deviations from the conventional might be more effective for changes in audience, purpose, or context. The study assesses pharmaceutical sponsor presentations at the Food and Drug Administration (FDA) drug advisory committee meetings. Preliminary findings indicate the need for changes to FDA conflict-of-interest policies.

Journal
Technical Communication Quarterly
Published
2015-01-02
DOI
10.1080/10572252.2015.975955
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Citation Context

Cited by in this index (27)

  1. Journal of Business and Technical Communication
  2. Rhetoric Society Quarterly
  3. Rhetoric Society Quarterly
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  4. Journal of Business and Technical Communication
  5. IEEE Transactions on Professional Communication
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  7. Computers and Composition
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  9. Technical Communication Quarterly
  10. Written Communication
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  14. Journal of Business and Technical Communication
  15. Technical Communication Quarterly
  16. Technical Communication Quarterly
  17. Technical Communication Quarterly
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  19. Technical Communication Quarterly
  20. Written Communication
  21. Technical Communication Quarterly
  22. Journal of Technical Writing and Communication

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