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This work presents an audit study of Apple News as a sociotechnical newscuration system that exercises gatekeeping power in the media. We examine themechanisms behind Apple News as well as the content presented in the app,outlining the social, political, and economic implications of both aspects. Wefocus on the Trending Stories section, which is algorithmically curated, andthe Top Stories section, which is human-curated. Results from a crowdsourcedaudit showed minimal content personalization in the Trending Stories section,and a sock-puppet audit showed no location-based content adaptation. Finally,we perform an extended two-month data collection to compare the human-curatedTop Stories section with the algorithmically curated Trending Stories section.Within these two sections, human curation outperformed algorithmic curation inseveral measures of source diversity, concentration, and evenness. Furthermore,algorithmic curation featured more "soft news" about celebrities andentertainment, while editorial curation featured more news about policy andinternational events. To our knowledge, this study provides the firstdata-backed characterization of Apple News in the United States.

Auditing News Curation Systems: A Case Study Examining Algorithmic and Editorial Logic in Apple News