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.
| Original language | English |
|---|---|
| Number of pages | 28 |
| Journal | Communication Research |
| DOIs | |
| Publication status | E-pub ahead of print - 14 Feb 2024 |
Scopus Subject Areas
- Communication
- Language and Linguistics
- Linguistics and Language
User-Defined Keywords
- algorithm
- automated journalism
- credibility
- machine authorship
- meta-analysis
- news evaluation
