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• Date of publication Aug 10, 2026 Category: Article

  User perceptions of incidental exposure to science content on social media — a qualitative study

  by Yannic Meier

  So far, incidental exposure (IE) to science information has been largely overlooked although science information can inform individually and societally relevant decisions. Semi-structured interviews with 19 social media users revealed that most participants believed IE to science information being largely algorithmically driven. Participants reported that content processing and engagement heavily depend on personal relevance and interest while content engagement is mostly passive. Participants commonly relied on trust, familiarity, and verification strategies to assess credibility as they were aware of misinformation. Although scarcely reported, IE to science information can inform decision-making. This exploratory study highlights shared mechanisms of IE across domains and provides a foundation for future quantitative research.

  Volume 25 • Issue 6 • 2026

• Date of publication May 25, 2026 Category: Article

  AI talking science: Experimental studies on the perception of AI-based chatbots as sources of science-based information

  by Esther Greussing , Friederike Hendriks , Dr Aike C. Horstmann , Yannic Meier , Bianca Nowak , Rainer Bromme

  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.

  Volume 25 • Issue 3 • 2026