As more news articles are written via collaboration between journalists and algorithms, questions have arisen regarding how automation influences the way that news is processed and evaluated by audiences. Informed by expectancy violation theory and the MAIN model, two experimental studies were conducted that examined the effect of purported machine authorship on perceptions of news credibility. Study One (N = 129) revealed that news attributed to a machine is perceived as less credible than news attributed to a human journalist. Study Two (N = 182) also observed negative effects of machine authorship through the indirect pathway of source anthropomorphism and negative expectancy violations, with evidence of moderation by prior recall of robotics also observed. The theoretical and practical implications of these findings are discussed.
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T. Franklin Waddell (2017) studied this question.
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