Large-scale digital signatures of emotional response to the COVID-19 vaccination campaign
EPJ Data Science(2024)
Abstract
The same individuals can express very different emotions in online social media with respect to face-to-face interactions, partially because of intrinsic limitations of the digital environments and partially because of their algorithmic design, which is optimized to maximize engagement. Such differences become even more pronounced for topics concerning socially sensitive and polarizing issues, such as massive pharmaceutical interventions. Here, we investigate how online emotional responses change during the large-scale COVID-19 vaccination campaign with respect to a baseline in which no specific contentious topic dominates. We show that the online discussions during the pandemic generate a vast spectrum of emotional response compared to the baseline, especially when we take into account the characteristics of the users and the type of information shared in the online platform. Furthermore, we analyze the role of the political orientation of shared news, whose circulation seems to be driven not only by their actual informational content but also by the social need to strengthen one’s affiliation to, and positioning within, a specific online community by means of emotionally arousing posts. Our findings stress the importance of better understanding the emotional reactions to contentious topics at scale from digital signatures, while providing a more quantitative assessment of the ongoing online social dynamics to build a faithful picture of offline social implications.
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Key words
Computational social science,Socio-technical systems,Exceptional events,COVID-19 vaccination,Emotions
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