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)
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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