Algorithms in the newsroom? News readers’ perceived credibility and selection of automated journalism

Abstract

Automated journalism, the autonomous production of journalistic content through computer algorithms, is increasingly prominent in newsrooms. This enables the production of numerous articles, both rapidly and cheaply. Yet, how news readers perceive journalistic automation is pivotal to the industry, as, like any product, it is dependent on audience approval. As audiences cannot verify all events themselves, they need to trust journalists’ accounts, which make credibility a vital quality ascription to journalism. In turn, credibility judgments might influence audiences’ selection of automated content for their media diet. Research in this area is scarce, with existing studies focusing on national samples and with no previous research on ‘combined’ journalism – a relatively novel development where automated content is supplemented by human journalists. We use an experiment to investigate how European news readers ( N = 300) perceive different forms of automated journalism in regard to message and source credibility, and how this affects their selection behavior. Findings show that, in large part, credibility perceptions of human, automated, and combined content and source(s) may be assumed equal. Only for sports articles was automated content perceived significantly more credible than human messages. Furthermore, credibility does not mediate the likelihood of news readers to either select or avoid articles for news consumption. Findings are, among other things, explained by topic-specific factors and suggest that effects of algorithms on journalistic quality are largely indiscernible to European news readers.