Media coverage plays a crucial role in shaping public perception of social movements. While attention-seeking protest tactics meet media selection criteria, they also risk distorting public perception. This study examines the German climate protest scene by comparing two key protest groups: Fridays for Future and Last Generation, the latter often criticized for its disruptive protest tactics. Building on the concept of mediatization, the protest paradigm, and agenda-setting theory, we analyze the mediated impact of different protest strategies on reader comments. Our quantitative content analysis includes 100 online news articles and 1,910 reader comments from three major German news sites (2019–2023). We find that articles about Last Generation focus more on protest actions and are less likely to prompt discussions about the climate issue among commentators. They are also more negative than those about Fridays for Future. However, journalistic evaluations are not directly reflected in the corresponding reader comments. These results suggest that non-normative and disruptive protest strategies could harm the discourse on climate change. Our findings are relevant for social movements and interest groups seeking to raise awareness of socially relevant issues such as climate protection and climate change. Additionally, this study contributes to understanding the dynamics between social movements, the media, and the public within the political communication system.
Gender inequality in screen industries across the world is well researched at both global and national scales. Evidence-based evaluation of inequality in these industries typically occurs at the level of annualised, aggregated statistical analysis in the form of summative data describing the number or proportion of women and gender minorities present in the screen sectors. Instead, this research study proceeds from the basis that gender inequality stems from unequal social relationships. We use Social Network Analysis (SNA) to evaluate the specific nature of collaboration networks in the German film industry over an eight-year period. We then extended the SNA research with career biographies, focussing our attention on the collaborative behaviours of the industry’s most influential beneficiaries: male film producers. Whereas previous research concluded there is no “pipeline” problem in the film industry because women graduate from film schools at statistically equitable levels, our findings reveal that the professional relationships formed between men at film school persist throughout their careers and operate to obstruct women’s opportunities.
Meinungsfreiheit ist nicht nur ein grundlegendes Menschenrecht, sondern bildet auch das Fundament liberaler Demokratien. Jedoch scheint bei einem größer werdenden Teil der Bevölkerung die Besorgnis um dieses Grundrecht zu wachsen – auch an Universitäten, an denen die freie Rede einen ganz besonderen Stellenwert einnimmt. Allerdings fehlt es trotz intensiver Debatten um „Political Correctness“ und „Cancel Culture“ bislang an Studien, die die Wahrnehmungen von Meinungsfreiheit durch Studierende an deutschen Universitäten sowie ihre Beteiligung an kontroversen Diskussionen auf breiter Basis empirisch untersuchen. Vor diesem Hintergrund geht der vorliegende Beitrag erstmals auf breiterer empirischer Basis der Frage nach, (1) wie Studierende die Meinungsfreiheit an deutschen Universitäten wahrnehmen, (2) wie intensiv sie sich an Diskussionen zu kontroversen Themen beteiligen und welche individuellen Merkmale (3) ihre Wahrnehmungen universitärer Meinungsfreiheit und (4) ihre Redebereitschaft in kontroversen Diskussionen beeinflussen. Die Ergebnisse einer quantitativen Online-Befragung einer disziplinär und regional heterogenen Stichprobe von Studierenden an deutschen Universitäten (N = 897), erhoben im Sommer 2023, zeigen, dass Studierende ein hohes Maß an Meinungsfreiheit in ihren Lehrveranstaltungen wahrnehmen. Allerdings finden kontroverse Diskussionen eher selten und vor allem in bestimmten Disziplinen statt und nur eine Minderheit von Studierenden beteiligt sich überhaupt daran. Zudem wird deutlich, dass die Wahrnehmung universitärer Meinungsfreiheit durch politische Einstellungen, Ängste vor Sanktionen durch Mitstudierende und Lehrende, aber auch die politische Kongruenz zu Mitstudierenden geprägt wird. Ob sich Studierende an kontroversen Diskussionen beteiligen, wird dagegen eher von politischem Interesse und Einstellungen sowie befürchteten Sanktionen durch Mitstudierende beeinflusst, wenn auch schwach. Mögliche Implikationen und Anknüpfungspunkte für zukünftige Forschung werden diskutiert.
Reliable scientific information is crucial for shaping public opinion and informing economic, social, and health-related decisions. While significant research has focused on detecting misinformation, the automated assessment of the overall quality of journalistic content remains largely unexplored. Addressing this gap, our study investigates whether different artificial intelligence approaches ranging from classical statistical methods (“bag-of-words”) to advanced large language models (LLMs) can assist in evaluating the quality of medical news articles based on ten established journalistic quality criteria. Drawing on a dataset of 240 articles and corresponding expert reviews, we show that machine learning models can indeed assess article quality with considerable accuracy. While several models fall short of human-level performance, fine-tuned LLMs perform well and, in most cases, match the level of agreement with a consolidated expert benchmark observed among individual human reviewers. The best-performing model, a fine-tuned GPT-4o model, detects poor-quality articles reliably when evaluated against expert assessments (macro-averaged F1: 0.69 vs. 0.57), suggesting its potential for use in editorial workflows, such as filtering incoming material or double-checking an already written text. Although our study focuses on medical journalism’s well-defined criteria, the approach likely holds promise for enhancing quality assurance in other areas of journalism and science communication where similar quality criteria exist.
Data donations have recently emerged as research method, partly enabled by legislation such as the GDPR. A relevant challenge they face are low participation rates, which can introduce bias and limit the potential of data donations to harness digital trace data for studying behavior in various contexts. We conducted an interdisciplinary scoping literature review to map research on participation in data donation studies, outlining factors that might discourage participation and strategies to address these issues. To ensure methodological clarity, data donations are defined by clear criteria: The donation is an active and unpaid, but at times incentivized, transfer of intangible, reproducible, and retrospective, trace data. Furthermore, data donations are voluntary and informed, and primarily motivated by contributing to the common good. Based on this definition, which also served as the inclusion criteria for our study, we analyzed 30 studies. Included literature predominantly focuses on health research and hypothetical scenarios, exploring attitudes rather than actual donations. Although the investigated literature is diverse, several factors are discussed to influence willingness to donate. These include respondent characteristics such as gender differences and technical skills, situational factors such as privacy concerns and motivations including egoism, study-related attributes including required data types and who receives the data, and societal-level factors such as contextual influences and culture. Strategies to increase willingness include general approaches like offering benefits and the right communication, as well as study design–related strategies, particularly cultivating trust, e.g., through credible collaborations and appropriate privacy protection.
