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Automated Journalism: A Meta-Analysis of Readers’ Perceptions of Human-Written in Comparison to Automated News

Author

Listed:
  • Andreas Graefe

    (Business Faculty, Macromedia University of Applied Sciences, Germany)

  • Nina Bohlken

    (Business Faculty, Macromedia University of Applied Sciences, Germany)

Abstract

This meta-analysis summarizes evidence on how readers perceive the credibility, quality, and readability of automated news in comparison to human-written news. Overall, the results, which are based on experimental and descriptive evidence from 12 studies with a total of 4,473 participants, showed no difference in readers’ perceptions of credibility, a small advantage for human-written news in terms of quality, and a huge advantage for human-written news with respect to readability. Experimental comparisons further suggest that participants provided higher ratings for credibility, quality, and readability simply when they were told that they were reading a human-written article. These findings may lead news organizations to refrain from disclosing that a story was automatically generated, and thus underscore ethical challenges that arise from automated journalism.

Suggested Citation

  • Andreas Graefe & Nina Bohlken, 2020. "Automated Journalism: A Meta-Analysis of Readers’ Perceptions of Human-Written in Comparison to Automated News," Media and Communication, Cogitatio Press, vol. 8(3), pages 50-59.
    • Handle: RePEc:cog:meanco:v8:y:2020:i:3:p:50-59
    DOI: 10.17645/mac.v8i3.3019
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