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

Open Access Journal | ISSN: 2183-2439

Review | Open Access

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


  • Andreas Graefe Business Faculty, Macromedia University of Applied Sciences, Germany
  • Nina Bohlken Business Faculty, Macromedia University of Applied Sciences, Germany


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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.

Keywords:  automated news; computational journalism; credibility; journalism; meta-analysis; perception; quality; review; robot journalism

Published:   10 July 2020


DOI: https://doi.org/10.17645/mac.v8i3.3019


© Andreas Graefe, Nina Bohlken. This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 license (http://creativecommons.org/licenses/by/4.0), which permits any use, distribution, and reproduction of the work without further permission provided the original author(s) and source are credited.