News Informatics: Engaging Individuals with Data-Rich News Content through Interactivity in Source, Medium, and Message

ACM Conference on Human Factors in Computing Systems (CHI)(2022)

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摘要
This paper introduces the concept of “news informatics” to refer to journalistic presentation of big data in online sites. For users to be engaged with such data-driven public information, it is important to incorporate interactive tools so that each person can extract personally relevant information. Drawing upon a communication model of interactivity, we designed a data-rich site with three different types of interactive features—namely, modality interactivity, message interactivity, and source interactivity—and empirically tested their relative and combined effects on user engagement and user experience with a 2 (modality) × 3 (source) × 2 (message) field experiment (N =166). Findings shed light on how interface designers, online news editors and journalists can maximize user engagement with data-rich news content. Certain interactivity combinations are found to be better than others, with a structural equation model (SEM) revealing the underlying theoretical mechanisms and providing implications for the design of news informatics.
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