Perceived Message Credibility Across Six AI-Generated News Stimuli with Different Visual Configurations: An Exploratory Evaluation
Chen Chen, Guili Li, Shuai Yuan, Yuxi LinAI-generated news is increasingly presented through combinations of text and visual content, making complete user-facing stimuli an important topic for credibility evaluation. This exploratory empirical evaluation examined perceived message credibility ratings across six implemented AI-generated news stimuli, organized by two selected stimulus domains—design industry and quantum computing—and three implemented presentation configurations: text only, an image with researcher-designated higher correspondence, and an image with researcher-designated lower correspondence. A total of 211 students from design-related disciplines evaluated all six stimuli in a fixed order, yielding 1266 ratings. Credibility ratings differed across the stimuli corresponding to the three implemented presentation configurations, F(1.95, 406.54) = 9.16, p < 0.001, partial η2 = 0.042, and the pattern of ratings across the implemented configurations differed between the selected stimulus domains, F(1.94, 404.48) = 14.94, p < 0.001, partial η2 = 0.067. Within the design-industry stimuli, the text-only stimulus was rated higher than the stimulus with a researcher-designated higher-correspondence image. Within the quantum-computing stimuli, both image-present stimuli were rated higher than the text-only stimulus, and the researcher-designated lower-correspondence image stimulus received the highest rating. The six implemented stimuli showed different credibility-rating patterns, underscoring the importance of considering visual attributes together with the content and presentation context in which they occur. Because story identity, presentation configuration, and serial position were not independently crossed, the findings describe the six implemented stimuli rather than isolated causal effects of visual presentation.