Podcasts elicit strong affective reactions that shape how listeners participate and evaluate. Drawing on Emotional Engagement Theory, we conceptualize emotion as a behavioural activation process that translates emotional expression into observable participation. We specify how this operates via the Elaboration Likelihood Model: utilitarian shows tend to invite more central-route processing (argument quality, informational utility), whereas hedonic shows more often engage peripheral-route cues (narrative tone, affective heuristics). We analysed a dataset of 108,464 Apple podcasts with 2,017,209 reviews using a transformer-based artificial intelligence emotion detection model. We found that low levels of anger, disgust, fear, sadness, and surprise, next to a dominant joy emotion, positively influenced the number of reviews a podcast receives for both utilitarian and hedonic podcasts. In contrast, achieving higher ratings requires minimizing these alternative emotions relative to joy. Some differences emerged between utilitarian and hedonic podcasts, with hedonic podcasts benefitting from a broader range of emotions, while balancing the effects of the mixed emotions in terms of increasing the number of reviews and reducing the average rating score.
Lee et al. (Fri,) studied this question.