The Impact of Machine Authorship on News Audience Perceptions : A Meta-Analysis of Experimental Studies

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

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Detail(s)

Original languageEnglish
Journal / PublicationCommunication Research
Publication statusOnline published - 14 Feb 2024

Abstract

The growing adoption of artificial intelligence in journalism has dramatically changed the way news is produced. Despite the recent proliferation of research on automated journalism, debate continues about how audiences perceive and evaluate news purportedly written by machines compared to the work of human authors. Based on a review of 30 experimental studies, this meta-analysis shows that machine authorship had a negative, albeit small, effect on credibility perceptions. Furthermore, machine authorship had a null effect on news evaluations, although this effect was significant and stronger (more negative) when (a) the news covered socio-political topics (vs. environmental topics) and (b) the actual source of the news articles was a machine (vs. a human). These findings are discussed in light of theoretical accounts of human–machine communication and practical implications for news media. © The Author(s) 2024.

Research Area(s)

  • automated journalism, machine authorship, algorithm, credibility, news evaluation, meta-analysis