Filter by keyword: Digital science communication

This study explores how YouTube content creators integrate scientific evidence into their videos by analyzing citation patterns across disciplines. The role of other alternative metrics is also considered. We apply Principal Component Analysis (PCA) to compare the citation count of 12,005 research articles from Biotechnology, Psychology, Astrophysics, and Ecology published between 2014 and 2023, including citations sourced from YouTube videos. Our findings provide a characterization of two principal components in evidence citation employed by various science communication stakeholders. The first component enhances a paper's visibility by driving social attention, while the second focuses on its social influence and impact, determined by the paper's quality and scientific relevance.

Previous research has suggested that incorporating emotional language and exemplars within inoculation messages could enhance their effectiveness in inducing resistance to climate change misinformation. We conducted a between-subject experiment with four conditions (negative narrative inoculation, positive narrative inoculation, didactic inoculation, and misinformation only condition) to test the effectiveness of inoculation. We found that didactic inoculation increased perceived threat significantly more than both types of narrative inoculations. However, there were no significant differences across these three types of inoculation messages in conferring resistance to misinformation regarding counterarguing against misinformation, belief in misinformation, perceived credibility of misinformation, or intention to share misinformation.

Micro-patronage provides a new model of funding for research communication. This article uses the Lingthusiasm podcast as a case study to describe how micro-patronage can work and some of the benefits and challenges involved. The authors draw on their own experience of micro-patronage to demonstrate how to create sustainable projects. They also discuss how it sits alongside university funding structures, while also providing a measure of independence from those structures.

This study examines the adoption of generative AI (genAI) tools in German university communication departments using 2023 and 2024 survey data. Adoption has significantly increased in 2024, particularly for text generation, with private universities leading the way. Efficiency gains are evident, but issues with factual accuracy and data privacy persist. The findings highlight a transition from cautious experimentation to mainstream integration of genAI in communication strategies, though ethical concerns remain. Communication departments face the challenge of balancing genAI’s efficiency benefits with the need to uphold quality, individuality, and privacy.

The advent of generative Artificial Intelligence (genAI) is expected to have a significant impact on journalism. In this study, we address whether this development could help mitigate the crisis in science journalism. We conducted semi-structured interviews with 30 German science journalists, asking them about the potential impact genAI may have on the news-making process (i.e., selection, production, and distribution). The results suggest that interviewees anticipate many future benefits associated with genAI, some believe that the technology is unlikely to worsen the crisis in science journalism, while others express concerns about potential negative consequences (e.g., job loss).

This study explores the role of ChatGPT in science-related information retrieval, building on research conducted in 2023. Drawing on online survey data from seven countries—Australia, Denmark, Germany, Israel, South Korea, Taiwan, and the United States—and two data collection points (2023 and 2024), the study highlights ChatGPT’s growing role as an information intermediary, reflecting the rapid diffusion of generative AI (GenAI) in general. While GenAI adoption is a global phenomenon, distinct regional variations emerge in the use of ChatGPT for science-related searches. Additionally, the study finds that a specific subset of the population is more likely to use ChatGPT for science-related information retrieval. Across all countries surveyed, science-information seekers report higher levels of trust in GenAI compared to non-users. They also exhibit a stronger understanding of how (Gen)AI works and, with some notable exceptions, show greater awareness of its epistemic limitations.

Based on an ethnography of the development and production of science YouTube videos – a collaboration between a German public broadcaster and social science scholars – we identify three intermediary steps through which recommendation algorithms shape science content on social media. We argue that algorithms induce changes to science content through the power they exert over the content's visibility on social media platforms. Change is driven by how practitioners interpret algorithms, infer content strategies to enhance visibility, and adjust content creation practices accordingly. By unpacking these intermediate steps, we reveal the nuanced mechanisms by which algorithms indirectly shape science content.

Most public audiences in Germany receive scientific information via a variety of (digital) media; in these contexts, media act as intermediaries of trust in science by providing information that present reasons for public audiences to place their trust in science. To describe this process, the study introduces the term “trust cues”. To identify such content-related trust cues, an explorative qualitative content analysis has been applied to German journalistic, populist, social, and other (non-journalistic) online media (“n” = 158). In total, “n” = 1,329 trust cues were coded. The findings emphasize the diversity of mediated trust, with trust cues being connected to dimensions of trust in science (established: expertise, integrity, benevolence; recently introduced: transparency, dialogue). Through this analysis, the study aims for a better understanding of mediated trust in science. Deriving this finding is crucial since public trust in science is important for individual and collective informed decision-making and crises management.

We conducted an experiment examining public response to scientists' use of different types of humor (satire, anthropomorphism, and a combination of the two) to communicate about AI on Twitter/X. We found that humor led to increased perceptions of humor, measured as increased mirth. Specifically, we found that combining anthropomorphism and satire elicited the highest levels of mirth. Further, reported mirth was positively associated with the perceived likability of the scientist who posted the content. Our findings indicate that mirth mediated the effects of the humor types on publics' perceptions that the scientist on social media was communicating information in an appropriate and legitimate way. Overall, this suggests that scientists can elicit mirth by using combining satire and anthropomorphic humor, which can enhance publics' perceptions of scientists. Importantly, publics' responses to harsh satire were not examined. Caution should be exercised when using satire due to potential backfire effects.

This study explores the subjective relevance and challenges of public engagement (PES) in science communication among professional university communicators based on 29 qualitative interviews in one German federal state. Despite recognizing its value, interviewees reveal significant uncertainties in understanding, objectives, and implementation of PES. They cite barriers such as reliance on scientists and control concerns. Surprisingly, social media is rarely considered for PES, with online engagement seen as difficult. This research highlights the complexities and challenges of PES in practice, emphasizing opportunities for optimized digital science communication strategies and clearer role structures between professionals and researchers to enhance PES.