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1. Introduction
The COVID-19 pandemic allowed the observation of information-seeking behavior and the effects of the availability of diverse information resources on the population and individuals. The acceptance of information might have had even an impact on the individual health, as a study on Brazil suggests (Burni et al., 2023). Social media platforms have emerged as crucial channels for diverse scientific communication content, addressing the unique informational demands that arise from times of crisis. Much misinformation was observed during the COVID-19 crisis online (Langguth et al., 2023) and responses applying AI have been developed (Nakov et al., 2022).
Recipients of medical and other crucial information face a considerable challenge in discerning its reliability and trustworthiness (Barnwal et al., 2019). The state of knowledge in a society depends on the available sources and during the COVID-19 crisis, there was much distorted information available (Campolino et al., 2022). The design of scientific communication artifacts is decisive for the human information-seeking behavior during crises (Soroya et al., 2021). Media creators, in particular, must learn to discern the different criteria by which their content and communication is consumed and judged by their followers (Jaki, 2021). The design of multimodal scientific information can be manifold and many options exist. Further exploration of optimal methods for disseminating scientific information are still necessary (Rodríguez Estrada and Davis, 2015).
This study zeroes in on dissecting online discussions surrounding the COVID-19 crisis, with a specific emphasis on science communication. The primary objective is to create a solution that aids creators of social media channels in navigating a large volume of feedback to their content, helping them filter out constructive feedback in regard to their own method of communication and the design of their products. Our focus is directed toward identifying and analyzing a distinct subset of comments posted in science communication channels in response to the presented content. Such an approach has not been carried out for science communication to the best of our knowledge. For the purposes of this study, 1.12 million tweets were collected, constituting comments from a network comprised of Brazilian scientists, governmental bodies, doctors and scientific communicators. It is noteworthy, that the majority of these comments are part of the broader discourse on the...