Filter by keyword: Digital science communication

Audiovisual communication methods such as digital storytelling can reach wide audiences to realise greater societal research impact. Increasingly, researchers embrace (or are expected to embrace) these approaches but often lack relevant skills. This paper draws on Horizon Europe-funded research where digital stories were developed in 20 European regions. Findings from a survey completed by the researchers highlight skills- and engagement-based challenges and explore how capacity to develop digital stories was built. The paper focuses on the role of digital storytelling in science communication, and the challenges researchers face in developing these outputs, including in ensuring meaningful participant involvement and the authentic representation of participants' voices within the final narratives. We discuss how to better support researchers to embrace digital storytelling as a science communication method, with recommendations for effective research impact.

AI-based chatbots offer new opportunities for communicating science-based information, but often fall short of established standards. We conducted two pre-registered experiments examining user perceptions of an AI-based chatbot providing information on nanoparticles in sunscreen. Study one (N = 508) tested whether a disclaimer about the chatbot's uncertain training data affected perceived source trustworthiness and information credibility. The results showed no significant effect of the disclaimer; perceptions were primarily influenced by users' prior attitudes. Study two (N = 1059) tested the evaluation of information on nanoparticles in sunscreen in an experiment with a 2 (source: scientist vs. AI-based chatbot) ×2 (presentation: static vs. dynamic) between-subjects design. The study showed that the scientist was evaluated as more trustworthy and the provided information seen as more credible compared to the AI-based chatbot. The two studies highlight the relevance of perceived objectivity in science and health communication, whether executed by humans or machines.

Multimodality in science communication has increased with the rise of digital communication affordances. Digital platforms enable greater integration of modes — text, visuals, and sound — within single messages. We argue that multimodality is particularly crucial for contested scientific issues, where viral spread, emotional persuasiveness, and personalisation are significant. We review empirical evidence and propose future research directions, thereby contributing to science communication in contested environments by examining the role of multimodality.

With the widespread use of AI-generated content (AIGC) on social media, its potential to spread misinformation poses threats to the public. Although AI disclosure is widely promoted as a transparency measure to prompt critical evaluation, its effectiveness in science communication remains controversial. This study conducted a within-subjects experiment (N = 433) to examine how AI disclosure affects perceived credibility of science communication texts and the moderating roles of readers' negative attitudes towards AI and audience involvement. The experiment manipulated AI disclosure labels and information veracity. The results revealed a truth-falsity crossover effect: AI disclosure significantly reduced the perceived credibility of correct information while unexpectedly increasing the perceived credibility of misinformation. Negative attitudes towards AI significantly moderated these effects, whereas audience involvement exerted only limited influence. These findings highlight the complex and sometimes counterproductive consequences of AI disclosure in science communication and suggest implications for cue-based processing, algorithm aversion, and the design of disclosure mechanisms.

The digitalisation of science communication has been widely promoted within the Open Science movement in Europe to foster the social impact of research, as well as a more participatory culture of science. Using semi-structured interviews, we explore Spanish women scientists' values and perceptions regarding digital science communication. Results highlight the social value of science communication as well as intrinsic motivation as factors to actively engage in disseminating, educating and promoting science digitally. Adopting Open Science principles, participants craft open access multimodal materials (e.g., educational short videos, podcasts), use supporting multimodal resources and digital tools, and engage in social media to reach broad audiences. Finally, we propose some policy recommendations and pedagogical guidelines in terms of digital literacy, digital genres, and science accommodation strategies to promote digital science communication.

TikTok has become a popular platform for science communication, particularly among younger audiences, allowing creators to reach broader audiences. However, concerns about the accuracy of science content shared on the platform have emerged, prompting this study to investigate the reliability of informal science communication by popular creators. Informal science communication is the casual sharing of scientific information on platforms like TikTok. The main objective is to assess how well this content adheres to established scientific principles and avoids misinformation. By analysing videos from creators with significant followings, we will evaluate their adherence to scientific accuracy and identify factors that influence it, such as the creators' backgrounds and platform algorithms. The findings will highlight trends in the accuracy of content, with some creators producing reliable information while others risk spreading misinformation. Ultimately, the research will provide recommendations for enhancing the accuracy of science content on TikTok, promoting critical thinking among viewers, and advancing informed science communication on social media.

This study investigates how Germany’s anti-lockdown and anti-vaccine protest movement, led mainly by the Querdenken network, allied with conspiracist and far-right groups, utilized scientific authority while opposing COVID-19 policy. We analyse posts published in 161 public Telegram channels using a computational pipeline that combines named-entity recognition, structural topic modeling, a BERT sentiment classifier, and an open-source large language model, Mixtral. We report that mentions of scientific information surged during periods of heightened policy uncertainty (e.g., national lockdowns and the vaccine-mandate debate), indicating tactical appeals to epistemic authority. References to science were initially scarce rather than hostile, but evolved into a selective, strategic endorsement: protest communities increasingly cherry-picked scientific claims to delegitimize containment measures (foremost, vaccination) while sidelining evidence contradicting their narrative. The findings show that, even among actors who reject official institutions, appeals to scientific language are strategically deployed as a discursive resource.

Scientists and experts using social media platforms to engage with the public risk negative public feedback, potentially harming their efforts. This paper addresses how negative user comments affect experts’ trustworthiness and the messages’ credibility depending on whether they frame their message as scientific versus anecdotal using an online study with a 2 (evidence type: scientific vs. anecdotal) x 3 (comments: neutral, negative-factual, negative-emotional) between-subjects design. The results suggest that relying on scientific evidence when engaging in emotionally charged discourses is beneficial. Negative-emotional comments have a significant negative impact on trustworthiness, which is especially pronounced when using anecdotal evidence.

Two studies, using real-time response measurement and interviews, explore how German recipients assess the trustworthiness of a voice-based communicative AI conveying science-related information with empathic and humorous expressions. In both a laboratory and an online study, humor was associated with short-term declines in trustworthiness, reflecting cultural expectations and appreciation of objectivity and neutrality. In contrast, empathic expressions are rated more trustworthy, but evoke less conspicuous effects. Cluster analysis identified four distinct patterns of evaluation, with two groups largely unaffected by affective cues and two skeptical of humor, underscoring the importance of personalization and adaptation in designing trustworthy communicative AI for science communication.