From SERPs to Sound
How Search Engine Result Pages and AI-generated Podcasts Interact to Influence User Attitudes on Controversial Topics
Junjie Wang (Student TU Delft)
Gaole He (TU Delft - Web Information Systems)
Alisa Rieger (GESIS - Leibniz Institute for the Social Sciences)
Ujwal Gadiraju (TU Delft - Web Information Systems)
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Abstract
Compared to search engine result pages (SERPs), AI-generated podcasts represent a relatively new and relatively more passive modality of information consumption, delivering narratives in a naturally engaging format. As these two media increasingly converge in everyday information-seeking behavior, it is essential to explore how their interaction influences user attitudes, particularly in contexts involving controversial, value-laden, and often debated topics. Addressing this need, we aim to understand how information mediums of present-day SERPs and AI-generated podcasts interact to shape the opinions of users. To this end, through a controlled user study (N = 483), we investigated user attitudinal effects of consuming information via SERPs and AI-generated podcasts, focusing on how the sequence and modality of exposure shape user opinions. A majority of users in our study corresponded to attitude change outcomes, and we found an effect of sequence on attitude change. Our results further revealed a role of viewpoint bias and the degree of topic controversiality in shaping attitude change, although we found no effect of individual moderators.
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