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Abstract

Although the Internet has become a major source for accessing news, there is little research regarding users' experience with news sites. We conducted an experiment to test a comprehensive model of user experience with news sites that was developed previously by means of an online survey. Level of adoption (novel or adopted site) was controlled with a between-subjects manipulation. We collected participants' answers to psychometric scales at 2 times: after presentation of 5 screenshots of a news site and directly after 10 minutes of hands-on experience with the site. The model was extended with the prediction of users' satisfaction with news sites as a high-level design goal. A psychometric measure of trust in news providers was developed and added to the model to better predict people's intention to use particular news sites. The model presented in this article represents a theoretically founded, empirically tested basis for evaluating news websites, and it holds theoretical relevance to user-experience research in general. Finally, the findings and the model are applied to provide practical guidance in design prioritization.

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Abstract

Although news websites are used by a large and increasing number of people, there is a lack of research within human-computer interaction regarding users' experience with this type of interactive technology. In the current research, existing measures of user-experience factors were identified and, using an online survey, answers to psychometric scales to measure website characteristics, need fulfillment, affective reactions, and constructs of technology acceptance and user experience were collected from regular users of news sites. A comprehensive user-experience model was formulated to explain acceptance and quality judgments of news sites. The main contribution of the current study is the application of influential models of user experience and technology acceptance to the domain of online news. By integrating both types of variable in a comprehensive model, the relationships between the types of variable are clarified both theoretically and empirically. Implications of the model for theory, further research, and system design are discussed.