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

• Main Authors: Andreas Graefe, Nina Bohlken
• Format: Article
• Language: English
• Published: Cogitatio 2020-07-01
• Series: Media and Communication
• Subjects: automated news; computational journalism; credibility; journalism; meta-analysis; perception; quality; review; robot journalism
• Online Access: https://www.cogitatiopress.com/mediaandcommunication/article/view/3019

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.