Filter by author: Monika Taddicken

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.

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.

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.

A potential decline in public trust in science has often been linked to digital media environments, which serve as intermediaries of trust by providing cues for why (not) to trust science. This study examines whether exposure to trust cues in content affects public trust in science (across population groups). The study employs a mixed-method design, combining content analysis (“n” = 906) and panel survey data (“n” = 1,030) in Germany. The findings reveal that exposure to trust cues in certain media predicts public trust in science. Variations across trust groups indicate a nuanced nature of trust-assessing processes in digital media environments.

A guiding theory for a continuous and cohesive discussion regarding generative artificial intelligence (GenAI) in science communication is still unavailable. Here, we propose a framework for characterizing, evaluating, and comparing AI-based information technologies in the context of critical engagement with scientific information in online environments. Hierarchically constructed, the framework observes technological properties, user experience, content presentation, and the context in which the technology is being used. Understandable and applicable for non-experts in AI systems, the framework affords a holistic yet practical assessment of various AI-based information technologies, providing both a reflection aid and a conceptual baseline for scholarly references.

Citizen science opens the scientific knowledge production process to societal actors. In this novel collaboration process, scientists and citizens alike face the challenge of new tasks and functions, eventually resulting in changing roles. Role theory provides a way of conceptualizing the roles that people take in communication and interaction. We use role theory to create a framework that identifies scientists' and citizens' tasks in citizen science projects, main aims of communication, spaces they interact in, and their roles — thus providing a structured way to capture communication and interaction in and about CS for further scientific reflection and practical application.

Internet technologies and specifically social media have drastically changed science communication. The public no longer merely consume science-related information but participate (for example, by rating and disseminating) and generate their own content. Likewise, scientists are no longer dependent on journalists as gatekeepers to spreading relevant information. This paper identifies and reflects on relevant theoretical strands that help to inform theoretical frameworks and research agendas. Therefore, we discuss the technological structures and resulting affordances, a new knowledge order and its actors, as well as trust and rationality as important constructs.

Expert debates have become a popular form to inform the public about scientific issues. To deepen our knowledge about individuals who attend such formats and to investigate what they expect of the dissemination of science, this study analyzes the attendants of scientific expert debates and their expectations. Cluster analysis is applied to survey data (n=358) to explore whether distinct segments may be distinguishable within this supposedly homogeneous audience. Four different segments were identified and, overall, the findings indicate that attendants expect science communication to not only present scientific findings comprehensibly and from different perspectives, but also to create everyday life applicability, whereas interacting with scientists is of less interest.

The measurement and analysis of people's knowledge on scientific topics, such as climate change, is challenging for researchers. One reason is that objectives are multi-dimensional and that probability is inherent. Moreover, uncertainties can exist on the individual's level among the public, but are rarely grasped by existing scales. Therefore, researchers must thoroughly consider what to measure and how. This paper theorizes five different dimensions of climate change knowledge. Three response scales including different degrees of confidence are applied on data from a German online survey (n=935); empirical results of multivariate regression analyses on attitudes are compared. Results highlight the importance of distinctively measuring dimensions and types of knowledge.

How users discuss climate change online is one of the crucial questions (science) communication scholars address nowadays. This study contributes by approaching the issue through the theoretical concept of online public arenas. The diversity of topics and perceptions in the climate change discourse is explored by comparing different arenas. German journalistic articles and their reader comments as well as scientific expert blogs are analyzed by quantitative manual and automated content analysis (n=5,301). Findings demonstrate a larger diversity of topics and interpretations in arenas with low barriers to communication. Overall, climate change skepticism is rare, but mostly present in lay publics.