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

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

Media and Communication, 2020, vol. 8, issue 3, 50-59

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 (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:cog:meanco:v8:y:2020:i:3:p:50-59

DOI: 10.17645/mac.v8i3.3019

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