Machine Authorship In Situ Effect of news organization and news genre on news credibility

• Published in: Digital journalism Vol. 7; no. 5; pp. 635 - 657
• Main Authors: Liu, Bingjie, Wei, Lewen
• Format: Journal Article
• Language: English
• Published: Routledge 28.05.2019
• Subjects: automated journalism; credibility; interpretive news; machine heuristic; mind perception; news organization
• ISSN: 2167-0811; 2167-082X
• DOI: 10.1080/21670811.2018.1510740

News-writing bots have been applied in news production. However, findings remain equivocal about how machine authorship is received by readers. To understand the inconsistency in past findings, this study conducted a 2 (purported writer: human vs. machine) × 2 (news organization: the New York Times vs. Fox News) × 2 (news type: spot news vs. interpretive news) between-subjects online experiment (N = 355) to examine how the identity of news writers, human vs. machine, would impact the processing and evaluation of the news writer and the news as context varies. Findings suggest that machine-written news induced less emotional involvement and was perceived as more objective. However, machine writer was perceived as of less expertise compared with its human counterpart. On the selected issues (Obamacare, LGBT rights, and refugee admission), news purported to be released by Fox News was less trusted by the participants than the New York Times. For a media organization whose news was more trusted, utilizing news-writing bots enhanced perceived news objectivity. Otherwise, employing bots further reduced perception of the writer's trustworthiness and expertise. Furthermore, machine authorship enhanced perceived news credibility more prominently when writing a genre that demanded more information processing. Theoretical and practical implications are discussed.