Developing a standardized protocol for computational sentiment analysis research using health-related social media data.

Journal: Journal of the American Medical Informatics Association : JAMIA
PMID: 33355353

Abstract

OBJECTIVE: Sentiment analysis is a popular tool for analyzing health-related social media content. However, existing studies exhibit numerous methodological issues and inconsistencies with respect to research design and results reporting, which could lead to biased data, imprecise or incorrect conclusions, or incomparable results across studies. This article reports a systematic analysis of the literature with respect to such issues. The objective was to develop a standardized protocol for improving the research validity and comparability of results in future relevant studies.

Authors

  • Lu He
    University of California, Irvine, Irvine, CA, USA.
  • Tingjue Yin
    Department of Informatics, Donald Bren School of Information and Computer Science, University of California, Irvine, Irvine, California, USA.
  • Zhaoxian Hu
    University of California, Irvine, Irvine, CA, USA.
  • Yunan Chen
    University of California, Irvine, Irvine, CA, USA.
  • David A Hanauer
    Department of Pediatrics, University of Michigan Medical School, Ann Arbor, MI, USA; School of Information, University of Michigan, Ann Arbor, MI, USA. Electronic address: hanauer@med.umich.edu.
  • Kai Zheng
    University of California, Irvine, Irvine, CA, USA.

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