Automated Journalism: A Meta-Analysis of Readers’ Perceptions of Human-Written in Comparison to Automated News
Author(s) -
Andreas Graefe,
Nina Bohlken
Publication year - 2020
Publication title -
media and communication
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.804
H-Index - 19
ISSN - 2183-2439
DOI - 10.17645/mac.v8i3.3019
Subject(s) - readability , credibility , journalism , quality (philosophy) , perception , reading (process) , psychology , computer science , social psychology , political science , sociology , media studies , law , philosophy , epistemology , neuroscience , programming language
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.
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