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Automated Journalism: A Meta-Analysis of Readers’ Perceptions of Human-Written in Comparison to Automated News
[journal article]
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... view more
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.... view less
Keywords
journalism; news; automation; quality; recipient; perception; credibility
Classification
Communicator Research, Journalism
Impact Research, Recipient Research
Free Keywords
automated news; computational journalism; meta-analysis; review; robot journalism
Document language
English
Publication Year
2020
Page/Pages
p. 50-59
Journal
Media and Communication, 8 (2020) 3
Issue topic
Algorithms and Journalism: Exploring (Re)Configurations
ISSN
2183-2439
Status
Published Version; peer reviewed