Climate Protest—What is it good for? Linking news coverage on German climate movements and reader comments

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Bibliographic information


Cover of Volume: SCM Studies in Communication and Media Volume 15 (2026), Issue 3
Open Access Full access

SCM Studies in Communication and Media

Volume 15 (2026), Issue 3


Authors:
Publisher
Nomos, Baden-Baden
Copyright Year
2026
ISSN-Online
2192-4007
ISSN-Print
2192-4007

Chapter information


Open Access Full access

Volume 15 (2026), Issue 3

Climate Protest—What is it good for? Linking news coverage on German climate movements and reader comments


Authors:
ISSN-Print
2192-4007
ISSN-Online
2192-4007


Preview:

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.

Bibliography


  1. Amaya, A., Biemer, P. P., & Kinyon, D. (2020). Total error in a big data world: Adapting the TSE framework to big data. Journal of Survey Statistics and Methodology, 8(1), 89–119. https://doi.org/10.1093/jssam/smz056 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  2. Android.com. (2018, September 25). Technology for today’s world: Helping you reclaim a sense of balance. Retrieved from https://blog.google/products/android/technology-todays-world-helping-you-reclaim-sense-balance/ Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  3. Apple Inc. (2018, September 25). iOS 12 führt neue Funktionen zum Vermeiden von Unterbrechungen und zur Verwaltung der Screen Time ein [iOS 12 introduces new function to avoid interruptions and managing screen time]. Retrieved from https://www.apple.com/de/newsroom/2018/06/ios-12-introduces-new-features-to-reduce-interruptions-and-manage-screen-time/ Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  4. Aquisti, A. (2004, May 17). Privacy in electronic commerce and the economics of immediate gratification. Proceedings of the 5th ACM Conference on Electronic Commerce, New York, NY, USA. https://doi.org/10.1145/988772.988777 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  5. Araujo, T., Wonneberger, A., Neijens, P., & de Vreese, C. (2017). How much time do you spend online? Understanding and improving the accuracy of self-reported measures of internet use. Communication Methods and Measures, 11(3), 173–190. https://doi.org/10.1080/19312458.2017.1317337 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  6. Arksey, H., & O’Malley, L. (2005). Scoping studies: Towards a methodological framework. International Journal of Social Research Methodology, 8(1), 19–32. https://doi.org/10.1080/1364557032000119616 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  7. Baumgartner, S. E., Sumter, S. R., Petkevič, V., & Wiradhany, W. (2023). A novel iOS data donation approach: Automatic processing, compliance, and reactivity in a longitudinal study. Social Science Computer Review, 41(4), 1456–1472. https://doi.org/10.1177/08944393211071068 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  8. Bietz, M., Patrick, K., & Bloss, C. (2019). Data donation as a model for citizen science health research. Citizen Science: Theory and Practice, 4(1). https://doi.org/10.5334/cstp.178 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  9. Blassnig, S., Mitova, E., Pfiffner, N., & Reiss, M. V. (2023). Googling referendum campaigns: Analyzing online search patterns regarding Swiss direct-democratic votes. Media and Communication, 11(1), 19–30. https://doi.org/10.17645/mac.v11i1.6030 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  10. Boeschoten, L., Ausloos, J., Möller, J. E., Araujo, T., & Oberski, D. L. (2022). A framework for privacy preserving digital trace data collection through data donation. Computational Communication Research, 4(2), 388–423. https://doi.org/10.5117/CCR2022.2.002.BOES Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  11. Booth, A., Sutton, A., Clowes, M., & Martyn-St James, M. (2022). Systematic approaches to a successful literature review (3rd ed.). SAGE. Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  12. Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  13. Breuer, J., Kmetty, Z., Haim, M., & Stier, S. (2022). User-centric approaches for collecting Facebook data in the ‘post-API age’: Experiences from two studies and recommendations for future research. Information, Communication & Society, 26(14), 2649–2668. https://doi.org/10.1080/1369118X.2022.2097015 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  14. Buhr, L., Schicktanz, S., & Nordmeyer, E. (2022). Attitudes toward mobile apps for pandemic research among smartphone users in Germany: National survey. JMIR MHealth and UHealth, 10(1), 1–17. https://doi.org/10.2196/31857 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  15. Carrière, T. C., Boeschoten, L., Struminskaya, B., Janssen, H. L., Schipper, N. C. de, & Araujo, T. (2025). Best practices for studies using digital data donation. Quality & Quantity, 59(Suppl 1), 389–412. https://doi.org/10.1007/s11135-024-01983-x Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  16. de León, E., Votta, F., Jongerius, S., Mulder, J., Struminskaya, B., Araujo, T., & de Vreese, C. (2025). Can tailored recruitment messaging increase digital trace data donation compliance? International Journal of Social Research Methodology, 1–17. https://doi.org/10.1080/13645579.2025.2568497 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  17. Diethei, D., Niess, J., Stellmacher, C., Stefanidi, E., & Schöning, J. (2021). Sharing heartbeats: Motivations of citizen scientists in times of crises. In Y. Kitamura, A. Quigley, K. Isbister, T. Igarashi, P. Bjørn, & S. Drucker (Eds.), Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems (pp. 1–15). ACM. https://doi.org/10.1145/3411764.3445665 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  18. Dinev, T., McConnell, A. R., & Smith, H. J. (2015). Research commentary—Informing privacy research through information systems, psychology, and behavioral economics: Thinking outside the “APCO” box. Information Systems Research, 26(4), 639–655. https://doi.org/10.1287/isre.2015.0600 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  19. European Parliament and the Council of the European Union. (2016, April 27). On the protection of natural persons with regard to the processing of personal data and on the free movement of such data (General data protection regulation). Retrieved from https://eur-lex.europa.eu/eli/reg/2016/679/oj Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  20. Gil-López, T., Christner, C., León, E. de, Makhortykh, M., Urman, A., Maier, M., & Adam, S. (2023). Do (not!) track me: Relationship between willingness to participate and sample composition in online information behavior tracking research. Social Science Computer Review, 41(6), 2274–2292. https://doi.org/10.1177/08944393231156634 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  21. Gomez Ortega, A., Bourgeois, J., & Kortuem, G. (2021). Towards designerly data donation. In Adjunct Proceedings of the 2021 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2021 ACM International Symposium on Wearable Computers (pp. 496–501). ACM. https://doi.org/10.1145/3460418.3479362# Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  22. Groves, R. M., Cialdini, R. B., & Couper, M. P. (1992). Understanding the decision to participate in a survey. Public Opinion Quarterly, 56, 475–495. https://doi.org/10.1086/269338 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  23. Haim, M., Graefe, A., & Brosius, H. B. (2018). Burst of the filter bubble? Digital Journalism, 6(3), 330–343. https://doi.org/10.1080/21670811.2017.1338145 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  24. Haim, M., & Hase, V. (2023). Computational Methods und Tools für die Erhebung und Auswertung von Social-Media-Daten [Computational methods and tools for social media data collection and analysis]. In S. Stollfuß, L. Niebling, & F. Raczkowski (Eds.), Handbuch Digitale Medien und Methoden (pp. 1–20). Springer Fachmedien Wiesbaden. https://doi.org/10.1007/978-3-658-36629-2_41-1 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  25. Hakobyan, O., Hillmann, P. J., Martin, F., Böttinger, E., & Drimalla, H. (2025). Development and evaluation of Dona, a privacy-preserving donation platform for messaging data from WhatsApp, Facebook, and Instagram. Behavior Research Methods, 57(3), 94. https://doi.org/10.3758/s13428-024-02593-z Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  26. Hase, V., Ausloos, J., Boeschoten, L., Pfiffner, N., Janssen, H., Araujo, T., Carrière, T., de Vreese, C., Haßler, J., Loecherbach, F., Kmetty, Z., Möller, J., Ohme, J., Schmidbauer, E., Struminskaya, B., Trilling, D., Welbers, K., & Haim, M. (2024). Fulfilling data access obligations: How could (and should) platforms facilitate data donation studies? Internet Policy Review, 13(3). https://doi.org/10.14763/2024.3.1793 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  27. Hase, V., & Haim, M. (2024). Can we get rid of bias? Mitigating systematic error in data donation studies through survey design strategies. Computational Communication Research, 6(2), 1–29. https://doi.org/10.5117/CCR2024.2.2.HASE Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  28. Hendricks-Sturrup, R., & Lu, C. Y. (2023). An assessment of perspectives and concerns among research participants of childbearing age regarding the health-relatedness of data, online data privacy, and donating data to researchers: Survey study. Journal of Medical Internet Research, 25. https://doi.org/10.2196/41937 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  29. Hendricks-Sturrup, R., Zhang, F., & Lu, C. Y. (2022). A survey of research participants’ privacy-related experiences and willingness to share real-world data with researchers. Journal of Personalized Medicine, 12(11). https://doi.org/10.3390/jpm12111922 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  30. Hillebrand, K., Hornuf, L., Müller, B., & Vrankar, D. (2023). The social dilemma of big data: Donating personal data to promote social welfare. Information and Organization, 33(1). https://doi.org/10.1016/j.infoandorg.2023.100452 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  31. Howison, J., Wiggins, A., & Crowston, K. (2011). Validity issues in the use of social network analysis with digital trace data. Journal of the Association for Information Systems, 12(12), 767–797. https://doi.org/10.17705/1jais.00282 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  32. Juga, J., Juntunen, J., & Koivumäki, T. (2021). Willingness to share personal health information: Impact of attitudes, trust and control. Records Management Journal, 31(1), 48–59. https://doi.org/10.1108/RMJ-02-2020-0005 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  33. Karampela, M., Ouhbi, S., & Isomursu, M. (2019). Connected Health user willingness to share personal health data: Questionnaire study. Journal of Medical Internet Research, 21(11). https://doi.org/10.2196/14537 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  34. Kaspar, K. (2020). Motivations COVID-19 for social distancing and app use as complementary measures to combat the pandemic: Quantitative survey study. Journal of Medical Internet Research, 22(8). https://doi.org/10.2196/21613 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  35. Kellermeyer, L., Harnke, B., & Knight, S. (2018). Covidence and Rayyan. Journal of the Medical Library Association, 106(4). https://doi.org/10.5195/jmla.2018.513 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  36. Keusch, F. (2015). Why do people participate in web surveys? Applying survey participation theory to internet survey data collection. Management Review Quarterly, 65(3), 183–216. https://doi.org/10.1007/s11301-014-0111-y Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  37. Keusch, F., Bähr, S., Haas, G. C., Kreuter, F., & Trappmann, M. (2023). Coverage error in data collection combining mobile surveys with passive measurement using apps: Data from a German national survey. Sociological Methods & Research, 52(2), 841–878. https://doi.org/10.1177/0049124120914924 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  38. Keusch, F., Pankowska, P. K., Cernat, A., & Bach, R. L. (2024). Do you have two minutes to talk about your data? Willingness to participate and nonparticipation bias in Facebook data donation. Field Methods, 36(4), 279–293. https://doi.org/10.1177/1525822X231225907 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  39. Keusch, F., Struminskaya, B., Mulder, J., & Jongerius, S. (2024). Measuring physical activity in older adults through data donation: Consent rates, donation success, & bias. https://doi.org/10.31235/osf.io/fdg8t Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  40. Kmetty, Z., Stefkovics, Á., Számely, J., Deng, D., Kellner, A., Pauló, E., Omodei, E., & Koltai, J. (2024). Determinants of willingness to donate data from social media platforms. Information, Communication & Society, 28(7), 1324–1349. https://doi.org/10.1080/1369118X.2024.2340995 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  41. Kulzer, B., Heinemann, L., & Roos, T. (2022). Patients’ experience of new technologies and digitalization in diabetes care in Germany. Journal of Diabetes Science and Technology, 16(6), 1521–1531. https://doi.org/10.1177/19322968211041377 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  42. Levac, D., Colquhoun, H., & O’Brien, K. (2010). Scoping studies: Advancing the methodology. Implementation Science, 5(69). https://doi.org/10.1186/1748-5908-5-69 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  43. Marreiros, H., Tonin, M., Vlassopoulos, M., & Schraefel, M. C. (2017). “Now that you mention it”: A survey experiment on information, inattention and online privacy. Journal of Economic Behavior & Organization, 140, 1–17. https://doi.org/10.1016/j.jebo.2017.03.024 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  44. Maus, B., Salvi, D., & Olsson, C. M. (2020). Enhancing citizens trust in technologies for data donation in clinical research: Validation of a design prototype. Companion Proceedings of the 10th International Conference on the Internet of Things (IoT 2020). Advance online publication. https://doi.org/10.1145/3423423.3423430 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  45. Mezinska, S., Kaleja, J., Mileiko, I., Santare, D., Rovite, V., & Tzivian, L. (2020). Public awareness of and attitudes towards research biobanks in Latvia. BMC Medical Ethics, 21(1). https://doi.org/10.1186/s12910-020-00506-1 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  46. Moher, D., Shamseer, L., Clarke, M., Ghersi, D., Liberati, A., Petticrew, M., Shekelle, P., & Stewart, L. A. (2015). Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement. Systematic Reviews, 4(1). https://doi.org/10.1186/2046-4053-4-1 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  47. Munn, Z., Peters, M. D. J., Stern, C., Tufanaru, C., McArthur, A., & Aromataris, E. (2018). Systematic review or scoping review? Guidance for authors when choosing between a systematic or scoping review approach. BMC Medical Research Methodology, 18(1). https://doi.org/10.1186/s12874-018-0611-x Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  48. Nissenbaum, H. (2010). Privacy in context: Technology, policy, and the integrity of social life. Stanford University Press. https://doi.org/10.1515/9780804772891 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  49. Norberg, P., & Horne, D. (2007). The privacy paradox: Personal information disclosure intentions versus behaviors. Journal of Consumer Affairs, 41(1), 100–126. https://doi.org/10.1111/j.1745-6606.2006.00070.x Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  50. Ohme, J., & Araujo, T. (2022). Digital data donations: A quest for best practices. Patterns, 3(4). https://doi.org/10.1016/j.patter.2022.100467 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  51. Ohme, J., Araujo, T., Boeschoten, L., Freelon, D., Ram, N., Reeves, B. B., & Robinson, T. N. (2023). Digital trace data collection for social media effects research: APIs, data donation, and (screen) tracking. Communication Methods and Measures, 18(2), 124–141. https://doi.org/10.1080/19312458.2023.2181319 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  52. Ohme, J., Araujo, T., de Vreese, C., & Piotrowski, J. T. (2021). Mobile data donations: Assessing self-report accuracy and sample biases with the iOS Screen Time function. Mobile Media & Communication, 9(2), 293–313. https://doi.org/10.1177/2050157920959106 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  53. Pak, C., Cotter, K., & Thorson, K. (2022). Correcting sample selection bias of historical digital trace data: Inverse probability weighting (IPW) and type II Tobit model. Communication Methods and Measures, 16(2), 134–155. https://doi.org/10.1080/19312458.2022.2037537 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  54. Peters, M. D. J., Marnie, C., Tricco, A. C., Pollock, D., Munn, Z., Alexander, L., McInerney, P., Godfrey, C. M., & Khalil, H. (2020). Updated methodological guidance for the conduct of scoping reviews. JBI Evidence Synthesis, 18(10), 2119–2126. https://doi.org/10.11124/JBIES-20-00167 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  55. Pfiffner, N., & Friemel, T. N. (2023). Leveraging data donations for communication research: Exploring drivers behind the willingness to donate. Communication Methods and Measures, 17(3), 227–249. https://doi.org/10.1080/19312458.2023.2176474 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  56. Pilgrim, K., & Bohnet-Joschko, S. (2022). Effectiveness of digital forced-choice nudges for voluntary data donation by health self-trackers in Germany: Web-based experiment. Journal of Medical Internet Research, 24(2), 1–13. https://doi.org/10.2196/31363 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  57. Prainsack, B. (2019). Data donation: How to resist the iLeviathan. In J. Krutzinna & L. Floridi (Eds.), The ethics of medical data donation (pp. 9–22). Springer. https://doi.org/10.1007/978-3-030-04363-6_2 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  58. Scharkow, M. (2016). The accuracy of self-reported internet use—A validation study using client log data. Communication Methods and Measures, 10(1), 13–27. https://doi.org/10.1080/19312458.2015.1118446 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  59. Seltzer, E., Goldshear, J., Guntuku, S. C., Grande, D., Asch, D. A., Klinger, E. V., & Merchant, R. M. (2019). Patients’ willingness to share digital health and non-health data for research: A cross-sectional study. BMC Medical Informatics and Decision Making, 19(1). https://doi.org/10.1186/s12911-019-0886-9 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  60. Severin-Nielsen, M. K. (2023). Politicians’ social media usage in a hybrid media environment: A scoping review of the literature between 2008–2022. Nordicom Review, 44(2), 172–193. https://doi.org/10.2478/nor-2023-0010 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  61. Silber, H., Breuer, J., Beuthner, C., Gummer, T., Keusch, F., Siegers, P., Stier, S., & Weiß, B. (2022). Linking surveys and digital trace data: Insights from two studies on determinants of data sharing behaviour. Journal of the Royal Statistical Society Series a: Statistics in Society, 185(Supplement_2), S387–S407. https://doi.org/10.1111/rssa.12954 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  62. Silber, H., Breuer, J., Felderer, B., Gerdon, F., Stammann, P., Daikeler, J., Keusch, F., & Weiß, B. (2024). Asking for traces: A vignette study on acceptability norms and personal willingness to donate digital trace data. Social Science Computer Review. Advance online publication. https://doi.org/10.1177/08944393241305776 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  63. Skatova, A., & Goulding, J. (2019). Psychology of personal data donation. PloS One, 14(11), 1–20. https://doi.org/10.1371/journal.pone.0224240 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  64. Sleigh, J. (2018). Experiences of donating personal data to mental health research: An explorative anthropological study. Biomedical Informatics Insights, 10. https://doi.org/10.1177/1178222618785131 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  65. Stier, S., Breuer, J., Siegers, P., & Thorson, K. (2020). Integrating survey data and digital trace data: Key issues in developing an emerging field. Social Science Computer Review, 38(5), 503–516. https://doi.org/10.1177/0894439319843669 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  66. Strycharz, J., Meppelink, C., Zarouali, B., Araujo, T., & Voorveld, H. (2024). The blind spot in data donations: Who is (not) willing to donate digital data in social scientific research. Computational Communication Research, 6(2), 1–27. https://doi.org/10.5117/CCR2024.2.3.STRY Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  67. Susha, I., Grönlund, Å., & van Tulder, R. (2019). Data driven social partnerships: Exploring an emergent trend in search of research challenges and questions. Government Information Quarterly, 36(1), 112–128. https://doi.org/10.1016/j.giq.2018.11.002 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  68. Thaler, R. H. (2018). Nudge, not sludge. Science, 361(6401), 431. https://doi.org/10.1126/science.aau9241 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  69. Thaler, R. H., & Sunstein, C. R. (2008). Nudge: Improving decisions about health, wealth, and happiness. Yale Univ. Press. Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  70. Toepoel, V., Luiten, A., & Zandvliet, R. (2021). Response, willingness, and data donation in a study on accelerometer possession in the general population. Survey Practice, 14(1), 1–19. https://doi.org/10.29115/SP-2021-0005 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  71. Tricco, A. C., Lillie, E., Zarin, W., O’Brien, K. K., Colquhoun, H., Levac, D., Moher, D., Peters, M. D. J., Horsley, T., Weeks, L., Hempel, S., Akl, E. A., Chang, C., McGowan, J., Stewart, L., Hartling, L., Aldcroft, A., Wilson, M. G., Garritty, C., . . . Straus, S. E. (2018). Prisma extension for scoping reviews (PRISMA-ScR): Checklist and explanation. Annals of Internal Medicine, 169(7), 467–473. https://doi.org/10.7326/M18-0850 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  72. van Driel, I. I., Giachanou, A., Pouwels, J. L., Boeschoten, L., Beyens, I., & Valkenburg, P. M. (2022). Promises and pitfalls of social media data donations. Communication Methods and Measures, 16(4), 266–282. https://doi.org/10.1080/19312458.2022.2109608 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  73. Wedel, L., Ohme, J., & Araujo, T. (2024). Augmenting data download packages – Integrating data donations, video metadata, and the multimodal nature of audio-visual content. Advance online publication. https://doi.org/10.12758/mda.2024.08 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  74. Welbers, K., Loecherbach, F., Lin, Z., & Trilling, D. (2024). Anything you would like to share: Evaluating a data donation application in a survey and field study. Computational Communication Research, 6(2), 1–28. https://doi.org/10.5117/CCR2024.2.5.WELB Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  75. Xiong, Y., van der Wal, A., & Beyens, I. (2025). Improving participation in data donation studies: A systematic review of factors driving participation and evidence-informed best practices. Social Science Computer Review. Advance online publication. https://doi.org/10.1177/08944393251395958 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  76. Zannettou, S., Nemeth, O. N., Ayalon, O., Goetzen, A., Gummadi, K. P., Redmiles, E. M., & Roesner, F. (2023, January 12). Analyzing user engagement with TikTok’s short format video recommendations using data donations. Proceedings of the 2024 CHI Conference on Human Factors in Computing Systems (CHI ‘24). Association for Computing Machinery, New York, NY, USA (pp. 1–16). https://doi.org/10.1145/3613904.3642433 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  77.   Open Google Scholar DOI: 10.5771/2192-4007-2026-3-011
  78. Acerbi, A., Altay, S., & Mercier, H. (2022). Research note: Fighting misinformation or fighting for information? Harvard Kennedy School (HKS) Misinformation Review, 3, 1–15. Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  79. Bail, C. A. (2024). Can generative AI improve social science? Proceedings of the National Academy of Sciences, 121(21). https://doi.org/10.1073/pnas.2314021121 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  80. Bodó, B., Helberger, N., Eskens, S., & Möller, J. (2019). Interested in diversity: The role of user attitudes, algorithmic feedback loops, and policy in news personalization. Digital journalism, 7(2), 206–229. https://doi.org/10.1080/21670811.2018.1521292 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  81. Bornmann, L., Mutz, R., & Daniel, H.-D. (2010). A reliability-generalization study of journal peer reviews: A multilevel meta-analysis of inter-rater reliability and its determinants. PLoS ONE, 5(12). https://doi.org/10.1371/journal.pone.0014331 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  82. Breiman, L. (2001). Random forests. Machine Learning, 45, 5–32. https://doi.org/10.1023/A:1010933404324 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  83. Bucchi, M., & Mazzolini, R. G. (2003). Big science, little news: Science coverage in the Italian daily press, 1946–1997. Public Understanding of Science, 12(1), 7–24. https://doi.org/10.1177/0963662503012001413 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  84. Burla, L., Knierim, B., Barth, J., Liewald, K., Duetz, M., & Abel, T. (2008). From text to codings: Intercoder reliability assessment in qualitative content analysis. Nursing Research, 57(2), 113–117. https://doi.org/10.1097/01.NNR.0000313482.33917.7d Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  85. Cacciatore, M. A. (2021). Misinformation and public opinion of science and health: Approaches, findings, and future directions. Proceedings of the National Academy of Sciences, 118(15). https://doi.org/10.1073/pnas.1912437117 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  86. Carlson, M. (2015). The robotic reporter: Automated journalism and the redefinition of labor, compositional forms, and journalistic authority. Digital Journalism, 3(3), 416–431. https://doi.org/10.1080/21670811.2014.976412 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  87. Caswell, D., & Dörr, K. (2018). Automated journalism 2.0: Event-driven narratives: From simple descriptions to real stories. Journalism Practice, 12(4), 477–496. https://doi.org/10.1080/17512786.2017.1320773 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  88. Chang, Y., Wang, X., Wang, J., Wu, Y., Yang, L., Zhu, K., Chen, H., Yi, X., Wang, C., Wang, Y., Ye, W., Zhang, Y., Chang, Y., Yu, P.S., Yang, Q., & Xie, X. (2023). A survey on evaluation of large language models. ACM Transactions on Intelligent Systems and Technology, 15, 1–45. https://doi.org/10.1145/3641289 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  89. Chiang, W.-L., Zheng, L., Sheng, Y., Angelopoulos, A. N., Li, T., Li, D., Zhang, H., Zhu, B., Jordan, M., Gonzalez, J. E., & Stoica I. (2024). Chatbot arena: An open platform for evaluating LLMs by human preference. arXiv, arXiv:2403.04132. https://doi.org/10.48550/arXiv.2403.04132 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  90. Choi, S., Shin, H., & Kang, S.-S. (2021). Predicting audience-rated news quality: Using survey, text mining, and neural network methods. Digital Journalism, 9(1), 84–105. https://doi.org/10.1080/21670811.2020.1842777 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  91. Clark, F., & Illman, D. L. (2006). A longitudinal study of the New York Times science times section. Science Communication, 27(4), 496–513. https://doi.org/10.1177/1075547006288010 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  92. Cohen, S., Hamilton, J. T., & Turner, F. (2011). Computational journalism. Communications of the ACM, 54(10), 66–71. https://doi.org/10.1145/2001269.2001288 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  93. Cordero, J. M., Henn, T., Holtel, F., Sánchez Gómez, J. Á., Arenas, D., Šipka, A., & Vollmer, S. (2025). Developing effective and value-aligned AI tools for journalists: 12 critical questions to reflect upon. Journalism Practice, 1–20. https://doi.org/10.1080/17512786.2025.2465894 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  94. Davies, N. (2008). Flat earth news: An award-winning reporter exposes falsehood, distortion and propaganda in the global media. Chatto & Windus. Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  95. Diakopoulos, N. (2019). Automating the news: How algorithms are rewriting the media. Harvard University Press. https://doi.org/10.4159/9780674239302 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  96. Diakopoulos, N., Cools, H., Helberger, N., Li, C., Kung, E., & Rinehart, A. (2024). Generative AI in journalism: The evolution of newswork and ethics in a generative information ecosystem. Associated Press. https://doi.org/10.13140/RG.2.2.31540.05765 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  97. Dörr, K. N. (2016). Mapping the field of algorithmic journalism. Digital Journalism, 4(6), 700–722. https://doi.org/10.1080/21670811.2015.1096748 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  98. Fähnrich, B., Weitkamp, E., & Kupper, J. F. (2023). Exploring ‘quality’ in science communication online: Expert thoughts on how to assess and promote science communication quality in digital media contexts. Public Understanding of Science, 32(5), 605–621. https://doi.org/10.1177/09636625221148054 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  99. Feng, S. Y., Gangal, V., Wei, J., Chandar, S., Vosoughi, S., Mitamura, T., & Hovy, E. (2021). A survey of data augmentation approaches for NLP. arXiv preprint arXiv:2105.03075. https://doi.org/10.18653/v1/2021.findings-acl.84 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  100. Gilardi, F., Alizadeh, M., & Kubli, M. (2023). ChatGPT outperforms crowd workers for text-annotation tasks. Proceedings of the National Academy of Sciences, 120(30). https://doi.org/10.1073/pnas.2305016120 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  101. Gladney, G. A. (1996). How editors and readers rank and rate the importance of eighteen traditional standards of newspaper excellence. Journalism & Mass Communication Quarterly, 73(2), 319–331. https://doi.org/10.1177/107769909607300204 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  102. Gutiérrez Lopez, M., Porlezza, C., Cooper, G., Makri, S., MacFarlane, A., & Missaoui, S. (2023). A question of design: Strategies for embedding AI-driven tools into journalistic work routines. Digital Journalism, 11(3), 484–503. https://doi.org/10.1080/21670811.2022.2043759 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  103. Hameleers, M. (2019). Susceptibility to mis- and disinformation and the effectiveness of fact-checkers: Can misinformation be effectively combated? SCM Studies in Communication and Media, 8(4), 523–546. https://doi.org/10.5771/2192-4007-2019-4-523 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  104. Helberger, N., van Drunen, M., Moeller, J., Vrijenhoek, S., & Eskens, S. (2022). Towards a normative perspective on journalistic AI: Embracing the messy reality of normative ideals. Digital Journalism, 10(10), 1605–1626. https://doi.org/10.1080/21670811.2022.2152195 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  105. Hermida, A., & Simon, F. M. (2025). AI in the newsroom: Lessons from the adoption of The Globe and Mail’s Sophi. Journalism Practice, 19(10), 1–18. https://doi.org/10.1080/17512786.2025.2471781 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  106. Himma-Kadakas, M., & Ojamets, I. (2022). Debunking false information: Investigating journalists’ fact-checking skills. Digital Journalism, 10(5), 866–887. https://doi.org/10.1080/21670811.2022.2043173 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  107. Islam, M. R., Liu, S., Wang, X., & Xu, G. (2020). Deep learning for misinformation detection on online social networks: A survey and new perspectives. Social Network Analysis and Mining, 10(1). https://doi.org/10.1007/s13278-020-00696-x Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  108. Jindal, H., Mangla, M., & Singh, G. (2023, June 16–17). Fake news detection using machine learning. International Conference on Recent Developments in Cyber Security (pp. 375–385), Greater Noida, India. https://doi.org/10.1016/j.procs.2025.09.048 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  109. Kim, B., Xiong, A., Lee, D., & Han, K. (2021). A systematic review on fake news research through the lens of news creation and consumption: Research efforts, challenges, and future directions. PLoS ONE, 16(12). https://doi.org/10.1371/journal.pone.0260080 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  110. Kotenidis, E., & Veglis, A. (2021). Algorithmic journalism – current applications and future perspectives. Journalism and Media, 2(2), 244–257. https://doi.org/10.3390/journalmedia2020014 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  111. Kumar, S., Asthana, R., Upadhyay, S., Upreti, N., & Akbar, M. (2020). Fake news detection using deep learning models: A novel approach. Transactions on Emerging Telecommunications Technologies, 31(2). https://doi.org/10.1002/ett.3767 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  112. Latar, N. L. (2018). Robot journalism: Can human journalism survive?. World Scientific. https://doi.org/10.1142/10913 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  113. Lin, B., & Lewis, S. C. (2022). The one thing journalistic AI just might do for democracy. Digital Journalism, 10(10), 1627–1649. https://doi.org/10.1080/21670811.2022.2084131 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  114. Liu, X., He, L., Alanazi, E., Liu, E., Goss, A., & Gumireddy, L. (2025). Assessing the accuracy and explainability of using ChatGPT to evaluate the quality of health news. BMC Public Health, 25(1). https://doi.org/10.1186/s12889-025-23206-0 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  115. Liu, X., Li, Q., Nourbakhsh, A., Fang, R., Thomas, M., Anderson, K., ..., & Shah, S. (2016). Reuters tracer: A large scale system of detecting & verifying real-time news events from Twitter. In Proceedings of the 25th ACM International on Conference on Information and Knowledge Management (pp. 207–216). Association for Computing Machinery. https://doi.org/10.1145/2983323.2983363 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  116. Løvlie, A. S., Waagstein, A., & Hyldgård, P. (2023). “How trustworthy is this research?” Designing a tool to help readers understand evidence and uncertainty in science journalism. Digital Journalism, 11(3), 431–464. https://doi.org/10.1080/21670811.2023.2193344 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  117. LSE (London School of Economics and Political Science) (2025). JournalismAI Case Studies. Retrieved March 13, 2026, from https://airtable.com/appdaeDwFizD4RK0u/shrKhe7Js48HvBhmG/tblBcSZESOAuy5Q9A Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  118. Mahony, S., & Chen, Q. (2025). Concerns about the role of artificial intelligence in journalism, and media manipulation. Journalism, 26(9). https://doi.org/10.1177/14648849241263293 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  119. McCallum, A., & Nigam, K. (1998). A comparison of event models for naive Bayes text classification. In AAAI-98 Workshop on Learning for Text Categorization (pp. 41–48). AAAI Press. Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  120. McQuail, D. (1993). Media performance: Mass communication and the public interest. University of Toronto Press. https://doi.org/10.22230/cjc.1993v18n4a783 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  121. Meier, K. (2019). Quality in journalism. In T. P. Vos, F. Hanusch, D. Dimitrakopoulou, M. Geertsema-Sligh, & A. Sehl (Eds.), The International Encyclopedia of Journalism Studies. Wiley. https://doi.org/10.1002/9781118841570.iejs0041 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  122. Mellon, J., Bailey, J., Scott, R., Breckwoldt, J., Miori, M., & Schmedeman, P. (2024). Do AIs know what the most important issue is? Using language models to code open-text social survey responses at scale. Research & Politics, 11(1). https://doi.org/10.1177/20531680241231468 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  123. Møller, L. A., van Dalen, A., & Skovsgaard, M. (2025). A little of that human touch: How regular journalists redefine their expertise in the face of artificial intelligence. Journalism Studies, 26(1), 84–100. https://doi.org/10.1080/1461670X.2024.2412212 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  124. Noain Sánchez, A. (2022). Addressing the impact of artificial intelligence on journalism: The perception of experts, journalists and academics. Communication & Society, 35(3), 105–121. https://doi.org/10.15581/003.35.3.105-121 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  125. Nyhan, B., Porter, E., Reifler, J., & Wood, T. J. (2020). Taking fact-checks literally but not seriously? The effects of journalistic fact-checking on factual beliefs and candidate favorability. Political Behavior, 42(3), 939–960. https://psycnet.apa.org/doi/10.1007/s11109-019-09528-x Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  126. Oxman, A. D., Guyatt, G. H., Cook, D. J., Jaeschke, R., Heddle, N., & Keller, J. (1993). An index of scientific quality for health reports in the lay press. Journal of Clinical Epidemiology, 46, 987–1001. https://doi.org/10.1016/0895-4356(93)90166-x Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  127. Qin, C., Zhang, A., Zhang, Z., Chen, J., Yasunaga, M., & Yang, D. (2023). Is ChatGPT a general-purpose natural language processing task solver? arXiv, arXiv:2302.06476. https://doi.org/10.18653/v1/2023.emnlp-main.85 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  128. Reich, Z., & Godler, Y. (2014). A time of uncertainty: The effects of reporters’ time schedule on their work. Journalism Studies, 15(5), 607–618. https://doi.org/10.1080/1461670X.2014.882484 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  129. Reinhart, M. (2009). Peer review of grant applications in biology and medicine. Reliability, fairness, and validity. Scientometrics, 81(3), 789–809. https://doi.org/10.1007/s11192-008-2220-7 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  130. Rieger, J., Yanchenko, K., Ruckdeschel, M., von Nordheim, G., Kleinen-von Königslöw, K., & Wiedemann, G. (2024). Few-shot learning for automated content analysis: Efficient coding of arguments and claims in the debate on arms deliveries to Ukraine. SCM Studies in Communication and Media, 13(1), 72–100. https://doi.org/10.5771/2192-4007-2024-1-72 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  131. Rögener, W., & Wormer, H. (2017). Defining criteria for good environmental journalism and testing their applicability: An environmental news review as a first step to more evidence based environmental science reporting. Public Understanding of Science, 26(4), 418–433. https://doi.org/10.1177/0963662515597195 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  132. Salewski, L., Alaniz, S., Rio-Torto, I., Schulz, E., & Akata, Z. (2024). In-context impersonation reveals large language models’ strengths and biases. Advances in Neural Information Processing Systems, 36, 72044–72057. https://doi.org/10.48550/arXiv.2305.14930 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  133. Schäfer, M. S. (2023). The notorious GPT: Science communication in the age of artificial intelligence. JCOM: Journal of Science Communication, 22. https://doi.org/10.22323/2.22020402 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  134. Schäfer, M. S., Kremer, B., Mede, N. G., & Fischer, L. (2024). Trust in science, trust in ChatGPT? How Germans think about generative AI as a source in science communication. Journal of Science Communication, 23(9). https://doi.org/10.22323/2.23090204 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  135. Schwitzer, G. (2008). How do US journalists cover treatments, tests, products, and procedures? An evaluation of 500 stories. PLoS Medicine, 5(5). https://doi.org/10.1371/journal.pmed.0050095 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  136. Shanahan, M., McDonell, K., & Reynolds, L. (2023). Role play with large language models. Nature, 623(7987), 493–498. https://doi.org/10.1038/s41586-023-06647-8 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  137. Silva Luna, D., Broer, I., Bilandzic, H., Taddicken, M., Schuller, B. W., & Bürger, M. (2025). Quality in science communication with communicative artificial intelligence: A principle-based framework. Public Understanding of Science, 34(8). https://doi.org/10.1177/09636625251328854 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  138. Simon, F. M. (2024). Artificial intelligence in the news: How AI retools, rationalizes, and reshapes journalism and the public arena (tech. rep.). Tow Center for Digital Journalism, Columbia University. https://doi.org/10.7916/ncm5-3v06 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  139. Smith, D. E., Wilson, A. J., & Henry, D. A. (2005). Monitoring the quality of medical news reporting: Early experience with media doctor. Medical Journal of Australia, 183(4), 190–193. Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  140. https://doi.org/10.5694/j.1326-5377.2005.tb06992.x Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  141. Stray, J. (2019). Making artificial intelligence work for investigative journalism. Digital Journalism, 7(8), 1076–1097. https://doi.org/10.1080/21670811.2019.1630289 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  142. Summ, A., & Volpers, A.-M. (2016). What’s science? Where’s science? Science journalism in German print media. Public Understanding of Science, 25(7), 775–790. https://doi.org/10.1177/0963662515583419 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  143. Tankard, J. W., Jr., & Ryan, M. (1974). News source perceptions of accuracy of science coverage. Journalism Quarterly, 51(2), 219–225. https://doi.org/10.1177/107769907405100204 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  144. Tay, L. Q., Lewandowsky, S., Hurlstone, M. J., Kurz, T., & Ecker, U. K. (2024). Thinking clearly about misinformation. Communications Psychology, 2(1). https://doi.org/10.1038/s44271-023-00054-5 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  145. Thurman, N. (2019). Computational journalism. In K. Wahl-Jorgensen & T. Hanitzsch (Eds.), The Handbook of Journalism Studies (2nd ed., pp. 180–195). Routledge. Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  146. Van Dalen, A. (2012). The algorithms behind the headlines: How machine-written news redefines the core skills of human journalists. Journalism Practice, 6(5–6), 648–658. https://doi.org/10.1080/17512786.2012.667268 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  147. Wei, J., & Zou, K. (2019). EDA: Easy data augmentation techniques for boosting performance on text classification tasks. arXiv preprint arXiv:1901.11196. https://doi.org/10.18653/v1/D19-1670 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  148. West, J. D., & Bergstrom, C. T. (2021). Misinformation in and about science. Proceedings of the National Academy of Sciences, 118(15). https://doi.org/10.1073/pnas.1912444117 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  149. Wilson, A., Bonevski, B., Jones, A., & Henry, D. (2009). Media reporting of health interventions: Signs of improvement, but major problems persist. PLoS ONE, 4(3). https://doi.org/10.1371/journal.pone.0004831 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  150. Wolf, C. (2024). Journalismus und künstliche Intelligenz aus kommunikationswissenschaftlicher Perspektive: Chancen und Herausforderungen [Journalism and artificial intelligence from a communication science perspective: Opportunities and challenges]. In G. Hooffacker, W. Kenntemich, & U. Kulisch (Eds.), Neue Plattformen – neue Öffentlichkeiten: KI, Krisen und Journalismus (pp. 9–29). Springer Fachmedien. https://doi.org/10.1007/978-3-658-44659-8_2 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  151. Wormer, H. (2011). Improving health care journalism. In G. Gigerenzer & J. A. Muir Gray (Eds.), Better doctors, better patients, better decisions: Envisioning Health Care 2020 (pp. 169–188). MIT Press. https://doi.org/10.7551/mitpress/9143.003.0016 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  152. Wu, S. (2024). Journalists as individual users of artificial intelligence: Examining journalists’ “value-motivated use” of ChatGPT and other AI tools within and without the newsroom. Journalism. https://doi.org/10.1177/14648849241303047 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  153. Wu, S., Irsoy, O., Lu, S., Dabravolski, V., Dredze, M., Gehrmann, S., Kambadur, P., Rosenberg, D., & Mann, G. (2023). BloombergGPT: A large language model for finance. arXiv, arXiv:2303.17564. https://doi.org/10.48550/arXiv.2303.17564 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  154. Zhang, H. (2004). The optimality of naive Bayes. In V. Barr & Z. Markov (Eds.), Proceedings of the Seventeenth International Florida Artificial Intelligence Research Society Conference (FLAIRS 2004) (pp. 562–567). AAAI Press. Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  155. Ziems, C., Held, W., Shaikh, O., Chen, J., Zhang, Z., & Yang, D. (2024). Can large language models transform computational social science? Computational Linguistics, 50, 237–291. https://doi.org/10.1162/coli_a_00502 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  156.   Open Google Scholar DOI: 10.5771/2192-4007-2026-3-012
  157. Amitay, G., Asraf, K., Elisha, E., Farber, S., Peleg-Koriat, I., & Yaron-Antar, A. (2025). Freedom of expression in Israeli campuses and social media during the war with Hamas. Journal of Higher Education Policy and Management, 48(1), 37–56. https://doi.org/10.1080/1360080X.2025.2535028 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  158. Armingeon, K. (2001). Fachkulturen, soziale Lage und politische Einstellungen der Studierenden der Universität Bern. Universität Bern. Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  159. Arzheimer, K. (2009). Gewichtungsvariation. In H. Schoen, H. Rattinger, & O. Gabriel (Hrsg.), Vom Interview zur Analyse (S. 361–388). Nomos. Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  160. Barendt, E. (2010). Academic freedom and the law: A comparative study. Hart Publishing. Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  161. Bar-Tal, D. (2017). Self-censorship as a socio-political-psychological phenomenon: Conception and research. Advances in Political Psychology, 38(S1), 37–65. https://doi.org/10.1111/pops.12391 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  162. Baumeister, R. F., & Leary, M. R. (1995). The need to belong: Desire for interpersonal attachments as a fundamental human motivation. Psychological Bulletin, 117(3), 497–529. https://doi.org/10.1037/0033-2909.117.3.497 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  163. Beierlein, C., Kemper, C. J., Kovaleva, A., & Rammstedt, B. (2014). Political efficacy Kurzskala (PEKS). ZIS. Open Access Repositorium für Messinstrumente. GESIS Leibniz Institut für Sozialwissenschaften. https://doi.org/10.6102/ZIS34 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  164. Berman, R. A. (2022). Inklusivität und die Grenzen der Wissenschaftsfreiheit: Zur Wiederkehr der »repressiven Toleranz«. In S. Kostner (Hg.), Wissenschaftsfreiheit. Warum dieses Grundrecht zunehmend umkämpft ist (S. 221–241). Nomos. https://doi.org/10.5771/9783748928058 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  165. Breuer, I. (2019, 21. Februar). Meinungsfreiheit. Wo die Grenzen des Sagbaren liegen [Audio-podcast-episode]. In Deutschlandfunk – Aus Kultur- und Sozialwissenschaften. Deutschlandfunk. https://www.deutschlandfunk.de/meinungsfreiheit-wo-die-grenzen-des-sagbaren-liegen-100.html Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  166. Burnett, A., Knighton, D., & Wilson, C. (2022). The self-censoring majority: How political Identity and ideology impacts willingness to self-censor and fear of isolation in the United States. Social Media + Society, 8(3). https://doi.org/10.1177/20563051221123031 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  167. Cialdini, R. B., & Goldstein, N. J. (2004). Social influence: Compliance and conformity. Annual Review of Psychology, 55, 591–621. https://doi.org/10.1146/annurev.psych.55.090902.142015 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  168. Cook, P., & Heilmann, C. (2013). Two types of self-censorship: Public and private. Political Studies, 61(1), 178–196. https://doi.org/10.1111/j.1467-9248.2012.00957.x Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  169. Decker, F., Best, V., Fischer, S., & Küppers, A. (2019). Vertrauen in Demokratie. Wie zufrieden sind die Menschen in Deutschland mit Regierung, Staat und Politik? Friedrich-Ebert-Stiftung. https://library.fes.de/pdf-files/fes/15621-20190822.pdf Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  170. Diehl, C., Revers, M., Traunmüller, R., Weidmann, N., & Wuttke, A. (2025). Students’ motives for restricting academic freedom: Viewpoint discrimination and prosocial concerns. PNAS, 122(47). https://doi.org/10.1073/pnas.2503804122 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  171. Döbele, C., Engels, J. N., Heinrich, R., Loew, N., Schläger, C., Simon, A. M., & Vitt, A.-K. (2023). Krisenerwachen. Wie blicken junge Wähler:innen auf Politik, Parteien und Gesellschaft? Friedrich-Ebert-Stiftung. https://library.fes.de/pdf-files/a-p-b/20355.pdf Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  172. Eikmanns, F., & Çay, Y. E. (2024, 30. Mai). Propalästina-Proteste an deutschen Unis. Wo endet die Meinungsfreiheit? taz. Abgerufen am 21. August 2024 von https://taz.de/Propalaestina-Proteste-an-deutschen-Unis/!6012172/ Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  173. Eppelsheim, P. (2022, 3. Juli). Cancel Culture an der Uni. Der Gesinnungsterror linker Aktivisten. Frankfurter Allgemeine Zeitung. Abgerufen am 3. Januar 2024 von https://www.faz.net/aktuell/politik/inland/linke-aktivisten-verhindern-vortrag-ueber-gen-der-an-humboldt-uni-18147133.html Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  174. Erich, N. (2020, 12. November). Meinungsfreiheit an Universitäten. Die Uni ist nichts für Schneeflöckchen. Zeit Online. Abgerufen am 3. Januar 2024 von https://www.zeit.de/kultur/2020-11/meinungsfreiheit-universitaeten-studie-cancel-culture-gesellschaft Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  175. Eßer, A. (2023). Studentische Fachkulturen: Lebensstile und politische Dispositionen. Eine Untersuchung der Studienfächer Rechtswissenschaft, VWL, BWL, Sozialwissenschaften, Philosophie, Mathematik und Biologie. Barbara Budrich. Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  176. Freedom House (2023). Freedom in the world 2023. Germany. Freedom House. Abgerufen am 11. Januar 2024 von https://freedomhouse.org/country/germany/freedom-world/2023 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  177. GESIS (o. D.). Links-Rechts Orientierung. GESIS Leibniz-Institut für Sozialwissenschaften. Abgerufen am 28. Januar 2024 von https://www.gesis.org/angebot/daten-aufbereiten-und-analysieren/question-link/links-rechts-orientierung Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  178. Garton Ash, T. (2016). Free speech: Ten principles for a connected world. Yale University Press. Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  179. Gibson, J. L., & Sutherland, J. L. (2023). Keeping your mouth shut: Spiraling self-censorship in the United States. Political Science Quarterly, 138(3), 361–376. https://doi.org/10.1093/psquar/qqad037 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  180. Grewenig, E., Lergetporer, P., Simon, L., Werner, K., & Woessmann, L. (2023). Can internet surveys represent the entire population? A practitioners’ analysis. European Journal of Political Economy, 78. https://doi.org/10.1016/j.ejpoleco.2023.102382 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  181. Grimm, J., Chojnacki, S., Moya Schreieder, N., El Ghoubashy, I., & Sixta, T. (2025). Deutsche Wissenschaft seit dem 7. Oktober: Selbstzensur und Einschränkungen unter Forschenden mit Nahostbezug. Working Papers Peace & Conflict Research, 2. Freie Universität Berlin. https://www.interact.fu-berlin.de/_media/WP202501_v0_7.pdf Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  182. Haake, K. (2021). Meinungs- und Lehrfreiheit – Was müssen Hochschulen aushalten? Bericht über die Tagung des Vereins zur Förderung des deutschen und internationalen Wissenschaftsrechts e.V. am 24.06.2021. Ordnung der Wissenschaft, 4, 257–264. Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  183. Hayes, A. F., Glynn, C. J., & Shanahan, J. (2005). Validating the willingness to self-censor scale: Individual differences in the effect of the climate of opinion expression. International Journal of Public Opinion Research, 17(4), 443–455. https://doi.org/10.1093/ijpor/edh072 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  184. Heil, L. U. (2016). Politikverdrossenheit. In L. U. Heil (Hg.), Gesättigte Demokratie. Ein marketingorientierter Alternativbegriff zur Politikverdrossenheit (S. 133–214). Springer VS. https://doi.org/10.1007/978-3-658-14326-8_3 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  185. Hillgruber, C. (2016). Die Meinungsfreiheit als Grundrecht der Demokratie: Der Schutz des demokratischen Resonanzbodens in der Rechtsprechung des BverfG. JuristenZeitung, 71(10), 495–501. http://www.jstor.org/stable/24768340 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  186. Hinz, T., Mozer, K., & Strauß, S. (2023). Durchführbarkeit und Qualität von rapid response research (R3HighEd). Umfragen bei Studierenden in Deutschland. Universität Konstanz. Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  187. Hoppe, K., Klingenberg, D., Thompson, V. E., Trautmann, F., & Vorbrugg, A. (2018). Worüber wir reden, wenn wir mit jemandem nicht reden wollen. Zum Spannungsverhältnis von Rassismuskritik und Meinungsfreiheit an der Universität. Movements. Journal for Critical Migration and Border Regime Studies, 4(1), 167–177. https://doi.org/10.64081/mvmnts-4.1-2509 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  188. Hübner, C., Eichhorn, J., Nicke, S., & Eilers, N. (2022). (NACH-)Wahlanalyse: Wie haben junge Deutsche 2021 bei der Bundestagswahl gewählt? Friedrich-Ebert-Stiftung. https://library.fes.de/pdf-files/pbud/19475.pdf Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  189. Infratest dimap (2024). ARD-DeutschlandTREND August 2024. Repräsentative Studie im Auftrag der ARD. Infratest dimap. https://www.infratest-dimap.de/umfragen-analysen/bundesweit/ard-deutschlandtrend/2024/august/ Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  190. Jaster, R., & Keil, G. (2021). Wen sollte man nicht an die Universität einladen? In E. Özmen (Hg.), Wissenschaftsfreiheit im Konflikt (S. 141–159). J. B. Metzler. https://doi.org/10.1007/978-3-662-62892-8_9 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  191. John, S. (2021). böll.brief. Demokratie & Gesellschaft #25. September 2021. Analyse der Bundestagswahl 2021. Heinrich Böll Stiftung. https://www.boell.de/sites/default/files/2021-10/BTW21_Analyse.pdf Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  192. Joint Committee on Human Rights. (2018). Freedom of speech in universities – Fourth report of session 2017–19 – Report, together with formal minutes relating to the report. HC 589 HL PAPER 111. House of Commons and House of Lords. https://publications.parliament.uk/pa/jt201719/jtselect/jtrights/589/589.pdf Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  193. Kinzelbach, K., Lindberg, S. I., & Lott, L. (2024). Academic Freedom Index 2024 Update. FAU Erlangen-Nürnberg and V-Dem Institute. https://doi.org/10.25593/open-fau-405. Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  194. Knight Foundation & Ipsos (2022). College student views on free expression and campus speech 2022: A look at key trends in student speech views since 2016. A Knight Foundation-Ipsos study from the Knight Free Expression Research Series. Knight Foundation & Ipsos. https://knightfoundation.org/reports/college-student-views-on-free-expression-and-campus-speech-2022/ Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  195. Köcher, R. (2019). Grenzen der Freiheit. Eine Dokumentation des Beitrags von Prof. Dr. Renate Köcher in der Frankfurter Allgemeinen Zeitung Nr. 119 vom 23. Mai 2019. Institut für Demoskopie Allensbach. https://www.ifd-allensbach.de/fileadmin/user_upload/FAZ_Mai2019_Meinungsfreiheit.pdf Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  196. Kostner, S. (2022). Hochschulen in den 2020er-Jahren. Intellektuelle Vielfalt oder intellektuelle Lockdowns? In S. Kostner (Hg.), Wissenschaftsfreiheit: Warum dieses Grundrecht zunehmend umkämpft ist (S. 7–30). Nomos. https://doi.org/10.5771/9783748928058 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  197. Lanius, D. (2020). Meinungsfreiheit und die kommunikative Strategie der Rechtspopulisten. In T. Schultz (Hg.), Was darf man sagen? Meinungsfreiheit im Zeitalter des Populismus (S. 75–112). Kohlhammer. Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  198. Leiner, D. J. (2019). Too fast, too straight, too weird: Non-reactive indicators for meaningless data in Internet surveys. Survey Research Methods, 13(3), 229–248. https://doi.org/10.18148/SRM/2019.V13I3.7403 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  199. Lindov, D. (2020). Teachers and politics. European Journal of Political Economy, 64. https://doi.org/10.1016/j.ejpoleco.2020.101902 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  200. Mansour, A. (2023, 8. September). Universitäten im Spannungsfeld von Meinungsfreiheit und Aktivismus. Jüdische Allgemeine. https://www.juedische-allgemeine.de/mei-nung/universitaeten-im-spannungsfeld-von-meinungsfreiheit-und-aktivismus/ Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  201. Matthes, J., Knoll, J., & von Sikorski, C. (2018). The “spiral of silence” revisited: A meta-analysis on the relationship between perceptions of opinion support and political opinion expression. Communication Research, 45(1), 3–33. https://doi.org/10.1177/0093650217745429 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  202. Meier, L. (2021). Eine soziologische Unschärferelation. Replik zum Aufsatz „Is Free Speech in Danger on University Campus? Some Preliminary Evidence from a Most Likely Case“ von Matthias Revers und Richard Traunmüller. KZfSS Kölner Zeitschrift für Soziologie und Sozialpsychologie, 73, 129–135. https://doi.org/10.1007/s11577-021-00736-0 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  203. Meltzer, C. E. (2017). Medienwirkung trotz Erfahrung. Der Einfluss von direkter und medial vermittelter Erfahrung eines Ereignisses. Springer VS. https://doi.org/10.1007/978-3-658-15579-7 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  204. Menzner, J., & Traunmüller, R. (2023). Subjective freedom of speech: Why do citizens think they cannot speak freely? Politische Vierteljahresschrift, 64, 155–181. https://doi.org/10.1007/s11615-022-00414-6 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  205. Merkley, E. (2020). Anti-intellectualism, populism, and motivated resistance to expert consensus. Public Opinion Quarterly, 84(1), 24–48. https://doi.org/10.1093/poq/nfz053 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  206. Naughton, K. A., Eastman, N., & Perrino, N. (2017). Speaking freely. What students think about expression at American colleges. FIRE. Foundation for Individual Rights in Education. https://www.fire.org/sites/default/files/2017/10/12154317/speaking-freely-2017-B-W.pdf Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  207. Neubaum, G., & Krämer, N. C. (2018). What do we fear? Expected sanctions for expressing minority opinions in offline and online communication. Communication Research, 45(2), 139–164. https://doi.org/10.1177/0093650215623837 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  208. Noelle-Neumann, E. (1974). The spiral of silence. A theory of public opinion. Journal of Communication, 24(2), 43–51. https://doi.org/10.1111/j.1460-2466.1974.tb00367.x Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  209. Noelle-Neumann, E. (1980). Die Schweigespirale. Öffentliche Meinung – unsere soziale Haut. Piper. Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  210. Norris, P. (2023). Cancel culture: Myth or reality? Political Studies, 71(1), 145–174. https://doi.org/10.1177/00323217211037023 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  211. Otto, L., & Bacherle, P. (2011). Politisches Interesse Kurzskala (PIKS) – Entwicklung und Validierung. Politische Psychologie, 1(1), 19–35. Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  212. Özmen, E. (Hg.) (2021). Wissenschaftsfreiheit im Konflikt. Grundlagen, Herausforderungen und Grenzen. J. B. Metzler. Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  213. Petersen, T. (2020). Forschungsfreiheit an deutschen Universitäten: Ergebnisse einer Umfrage unter Hochschullehrern. Kurzpräsentation. Akademie der Konrad-Adenauer-Stiftung. Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  214. Petersen, T. (2021a). Das geistige Klima an Universitäten. Ergebnisse einer Online-Befragung von Hochschullehrern. Institut für Demoskopie Allensbach. Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  215. Petersen, T. (2021b). Die Mehrheit fühlt sich gegängelt. Eine Dokumentation des Beitrags von Dr. Thomas Petersen in der Frankfurter Allgemeinen Zeitung Nr. 136 vom 16. Juni 2021. Institut für Demoskopie Allensbach. https://www.ifd-allensbach.de/fileadmin/kurzberichte_dokumentationen/FAZ_Juni2021_Meinungsfreiheit.pdf Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  216. Quiring, O., Jackob, N., Schemer, C., Jakobs, I., & Ziegele, M. (2020). „Das wird man doch noch sagen dürfen…“ – Wahrgenommene Sprechverbote und ihre Korrelate. In N. Jackob, O. Quiring, & M. Maurer (Hrsg.), Traditionen und Transformationen des Öffentlichen (S. 49–71). Springer VS. https://doi.org/10.1007/978-3-658-29321-5_3 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  217. Revers, M., & Traunmüller, R. (2020). Is free speech in danger on university campus? Some preliminary evidence from a most likely case. KZfSS Kölner Zeitschrift für Soziologie und Sozialpsychologie, 72, 471–497. https://doi.org/10.1007/s11577-020-00713-z Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  218. Rothut, S., Sacher, A.-L., Strohmeier, R., & Reinemann, C. (2023). Meinungsfreiheit in Gefahr? Wie politische Einstellungen und individuelle Erfahrungen die Wahrnehmung der Meinungsfreiheit in Deutschland prägen. Studies in Communication and Media, 12(1), 48–86. https://doi.org/10.5771/2192-4007-2023-1-48 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  219. Sacher, A., & Reinemann, C. (2025). What is freedom of speech? How citizens define and perceive the ‘Bulwark of Liberty’. The International Journal of Press/Politics. https://doi.org/10.1177/19401612251388182 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  220. Sachs, J. A. (2018, 16. März). The ‘campus free speech crisis’ is a myth. Here are the facts. The Washington Post. Abgerufen am 6. Januar 2024 von https://www.washingtonpost.com/news/monkey-cage/wp/2018/03/16/the-campus-free-speech-crisis-is-a-myth-here-are-the-facts/ Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  221. Sand, M., & Kunz, T. (2020). Gewichtung in der Praxis (April 2020, Version 1.0). GESIS – Leibniz-Institut für Sozialwissenschaften (GESIS-Survey Guidelines). https://doi.org/10.15465/gesis-sg_030 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  222. Schafer, J. L., & Graham, J. W. (2002). Missing data: Our view of the state of the art. Psychological Methods, 7(2), 147–177. https://doi.org/10.1037/1082-989X.7.2.147 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  223. Schieritz, M., & Scholz, A.-L. (2024, 17. Mai). Pro-Palästina-Demos: Gehen die Uni-Proteste zu weit? Zeit Online. Abgerufen am 21. August 2024 von https://www.zeit.de/2024/22/pro-palaestina-demos-universitaeten-gaza-proteste-israel Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  224. Scott-Baumann, A., & Perfect, S. (2021). Freedom of speech in universities: Islam, Charities and Counter-terrorism. Routledge. Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  225. Shell Jugendstudie. (2019). Zusammenfassung Shell Jugendstudie. Shell. Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  226. Statistisches Bundesamt. (2023). Statistischer Bericht. Statistik der Studierenden. Wintersemester 2022/2023. Erschienen am 8. August 2023. Statistisches Bundesamt. https://www.destatis.de/DE/Themen/Gesellschaft-Umwelt/Bildung-Forschung-Kultur/Hochschulen/Publikationen/Downloads-Hochschulen/statistischer-bericht-studierende-hochschulen-endg-2110410237005.xlsx?__blob=publicationFile Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  227. Statistisches Bundesamt. (2024). Bildung und Kultur. Studierende an Hochschulen – Fächersystematik – 2022. Übersicht 1. Fächergruppen, Studienbereiche und Studienfächer. Stand: WS 2022/2023. Statistisches Bundesamt. https://www.destatis.de/DE/Methoden/Klassifikationen/Bildung/studenten-pruefungsstatistik.pdf?__blob=publicationFile Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  228. Stevens, S., & Haidt, J. (2018a, 4. März). The skeptics are wrong Part 1: Attitudes about free speech on campus are changing. Heterodox Academy. Abgerufen am 23. Januar 2024 von https://heterodoxacademy.org/blog/skeptics-are-wrong-about-campus-speech/ Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  229. Stevens, S., & Haidt, J. (2018b, 11. März). The skeptics are wrong part 2: Speech culture on campus is changing. Heterodox Academy. Abgerufen am 23. Januar 2024 von https://heterodoxacademy.org/blog/the-skeptics-are-wrong-part-2/ Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  230. Taddicken, M. (2013). Online-Befragung. In W. Möhring & D. Schlütz (Hrsg.), Handbuch standardisierte Erhebungsverfahren in der Kommunikationswissenschaft (S. 201–217). Springer VS. https://doi.org/10.1007/978-3-531-18776-1_11 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  231. Traunmüller, R. (2022). Die »Cancel Culture«-Hypothese auf dem empirischen Prüfstand. In S. Kostner (Hg.), Wissenschaftsfreiheit: Warum dieses Grundrecht zunehmend umkämpft ist (S. 33–54). Nomos. https://doi.org/10.5771/9783748928058 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  232. Traunmüller, R. (2023). Testing the ‘campus cancel culture’ hypothesis, SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4392840 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  233. Traunmüller, R., & Revers, M. (2021). Meinungsfreiheit an der Universität: Unschärfen und Strohmänner (Antwort auf Lars Meier). KZfSS Kölner Zeitschrift für Soziologie und Sozialpsychologie, 73, 137–146. https://doi.org/10.1007/s11577-021-00758-8 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  234. Unzicker, K. (2018, 17. Juli). „Das wird man ja wohl noch sagen dürfen“ – Keine Meinungsfreiheit in Deutschland? Bertelsmann Stiftung. Blog Vielfalt leben – Gesellschaft gestalten. Abgerufen am 3. Januar 2024 von https://demokratie-und-zusammenhalt.de/2018/07/17/das-wird-man-ja-wohl-noch-sagen-duerfen-keine-meinungsfreiheit-in-deutschland/ Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  235. van Buuren, S. (2018). Flexible imputation of missing data. Chapman & Hall/CRC. https://stefvanbuuren.name/fimd/ Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  236. Villa, P.-I., Traunmüller, R., & Revers, M. (2021, 12. November). Lässt sich „Cancel Culture“ empirisch belegen? Impulse für eine pluralistische Fachdebatte. Bundeszentrale für politische Bildung. Abgerufen am 27. Januar 2024 von https://www.bpb.de/shop/zeitschriften/apuz/wissenschaftsfreiheit-2021/343228/laesst- sich-cancel-culture-empirisch-belegen/ Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  237. Vogel, F. (2019). „Meinungsfreiheit“ und ihre Grenzen an der Universität. Ein Kommentar. Navigationen – Zeitschrift für Medien- und Kulturwissenschaften, 19(2), 33–38. https://doi.org/10.25969/MEDIAREP/13816 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  238. Williams, K. D. (2007). Ostracism: The kiss of social death. Social and Personality Psychology Compass, 1(1), 236–247 https://doi.org/10.1111/j.1751-9004.2007.00004.x Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  239. Willnat, L., Lee, W., & Detenber, B. H. (2002). Individual-level predictors of public outspokenness: A test of the spiral of silence theory in Singapore. International Journal of Public Opinion Research, 14(4), 391–412. https://doi.org/10.1093/ijpor/14.4.391 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  240. Wintterlin, F., Frischlich, L., Boberg, S., Schatto-Eckrodt, T., Reer, F., & Quandt, T. (2021). Corrective actions in the information disorder. The role of presumed media influence and hostile media perceptions for the countering of distorted user-generated content. Political Communication, 38(6), 773–791. https://doi.org/10.1080/10584609.2021.1888829 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  241. YouGov (2018, 27. Juni). Are students really more hostile to free speech? YouGov. Abgerufen am 21. August 2024 von https://yougov.com/en-gb/articles/21051-are-students-really-more-hostile-free-speech Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  242. ZEIT-Stiftung (2024). Akademische Redefreiheit. Kurzbericht zu einer empirischen Studie an deutschen Hochschulen. https://read.zeit-stiftung.com/report_akademischeredefreiheit/ Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  243. Zhou, S., & Barbaro, N. (2023). Understanding campus expression across higher ed: Heterodox Academy‘s annual campus expression survey. Heterodox Academy. https://heterodoxacademy.org/reports/2022-campus-expression-survey-report/ Open Google Scholar DOI: 10.5771/2192-4007-2026-3-013
  244. Diehl, C., Revers, M., Traunmüller, R., Weidmann, N., & Wuttke, A. (2025). Students’ motives for restricting academic freedom: Viewpoint discrimination and prosocial concerns. PNAS, 122(47). https://doi.org/10.1073/pnas.2503804122 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-014
  245. Garton Ash, T. (2016). Free speech: Ten principles for a connected world. Yale University Press. Open Google Scholar DOI: 10.5771/2192-4007-2026-3-014
  246. Menzner, J., & Traunmüller, R. (2023). Subjective freedom of speech: Why do citizens think they cannot speak freely? Politische Vierteljahresschrift, 64, 155–181. https://doi.org/10.1007/s11615-022-00414-6 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-014
  247. Neubaum, G., & Krämer, N. C. (2018). What do we fear? Expected sanctions for expressing minority opinions in offline and online communication. Communication Research, 45(2), 139–164. Open Google Scholar DOI: 10.5771/2192-4007-2026-3-014
  248. Noelle-Neumann, E. (1974). The spiral of silence. A theory of public opinion. Journal of Communication, 24(2), 43–51. https://doi.org/10.1111/j.1460-2466.1974.tb00367.x Open Google Scholar DOI: 10.5771/2192-4007-2026-3-014
  249. Norris, P. (2023). Cancel culture: Myth or reality? Political Studies, 71(1), 145–174. https://doi.org/10.1177/00323217211037023 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-014
  250. Petersen, T. (2020). Forschungsfreiheit an deutschen Universitäten: Ergebnisse einer Umfrage unter Hochschullehrern. Kurzpräsentation [Research freedom at German universities: Results of a survey among university lecturers]. Akademie der Konrad-Adenauer-Stiftung. Open Google Scholar DOI: 10.5771/2192-4007-2026-3-014
  251. Petersen, T. (2021). Das geistige Klima an Universitäten. Ergebnisse einer Online-Befragung von Hochschullehrern [The intellectual climate at universities. Results of an online survey among university lecturers]. Institut für Demoskopie Allensbach. Open Google Scholar DOI: 10.5771/2192-4007-2026-3-014
  252. Revers, M., & Traunmüller, R. (2020). Is free speech in danger on university campus? Some preliminary evidence from a most likely case. KZfSS Kölner Zeitschrift für Soziologie und Sozialpsychologie, 72, 471–497. https://doi.org/10.1007/s11577-020-00713-z Open Google Scholar DOI: 10.5771/2192-4007-2026-3-014
  253. Rothut, S., Sacher, A.-L., Strohmeier, R., & Reinemann, C. (2023). Meinungsfreiheit in Gefahr? Wie politische Einstellungen und individuelle Erfahrungen die Wahrnehmung der Meinungsfreiheit in Deutschland prägen [Freedom of speech under threat? How political attitudes and individual experiences shape perceptions of freedom of speech in Germany]. Studies in Communication and Media, 12(1), 48–86. https://doi.org/10.5771/2192-4007-2023-1-48 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-014
  254. Sacher, A., & Reinemann, C. (2025). What is freedom of speech? The International Journal of Press/Politics. https://doi.org/10.1177/19401612251388182 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-014
  255. Scott-Baumann, A., & Perfect, S. (2021). Freedom of speech in universities: Islam, Charities and Counter-terrorism. Routledge. Open Google Scholar DOI: 10.5771/2192-4007-2026-3-014
  256. Wintterlin, F., Frischlich, L., Boberg, S., Schatto-Eckrodt, T., Reer, F., & Quandt, T. (2021). Corrective actions in the information disorder. Political Communication, 38(6), 773–791. https://doi.org/10.1080/10584609.2021.18 88829 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-014
  257. ZEIT-Stiftung (2024). Akademische Redefreiheit. Kurzbericht zu einer empirischen Studie an deutschen Hochschulen [Academic freedom of expression. Brief report on an empirical study at German universities]. https://read.zeit-stiftung.com/report_akademischeredefreiheit/ Open Google Scholar DOI: 10.5771/2192-4007-2026-3-014
  258. Zhou, S., & Barbaro, N. (2023). Understanding campus expression across higher ed. Heterodox Academy. Open Google Scholar DOI: 10.5771/2192-4007-2026-3-014
  259.   Open Google Scholar DOI: 10.5771/2192-4007-2026-3-014
  260. Andrews, K. T., & Caren, N. (2010). Making the news: Movement organizations, media attention, and the public agenda. American Sociological Review, 75(6), 841–866. https://doi.org/10.1177/0003122410386689 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  261. Berker, L. E., & Pollex, J. (2023). Explaining differences in party reactions to the Fridays for Future-movement – A qualitative comparative analysis (QCA) of parties in three European countries. Environmental Politics, 32(5), 755–792. https://doi.org/10.1080/09644016.2022.2127536 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  262. Boyle, M. P., McLeod, D. M., & Armstrong, C. L. (2012). Adherence to the protest paradigm: The influence of protest goals and tactics on news coverage in U.S. and international newspapers. The International Journal of Press/Politics, 17(2), 127–144. https://doi.org/10.1177/1940161211433837 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  263. Brehm, J., & Gruhl, H. (2024). Increase in concerns about climate change following climate strikes and civil disobedience in Germany. Nature Communications, 15(1). https://doi.org/10.1038/s41467-024-46477-4 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  264. Brouwer, C., Bolderdijk, J.-W., Cornelissen, G., & Kurz, T. (2022). Communication strategies for moral rebels: How to talk about change in order to inspire self-efficacy in others. WIREs Climate Change, 13(5). https://doi.org/10.1002/wcc.781 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  265. Brown, D. K., & Mourão, R. R. (2021). Protest coverage matters: How media framing and visual communication affects support for black civil rights protests. Mass Communication and Society, 24(4), 576–596. https://doi.org/10.1080/15205436.2021.1884724 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  266. Bugden, D. (2020). Does climate protest work? Partisanship, protest, and sentiment pools. Socius, 6. https://doi.org/10.1177/2378023120925949 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  267. Buzogány, A., & Scherhaufer, P. (2022). Framing different energy futures? Comparing Fridays for Future and Extinction Rebellion in Germany. Futures, 137. https://doi.org/10.1016/j.futures.2022.102904 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  268. Camaj, L. (2014). The consequences of attribute agenda-setting effects for political trust, participation, and protest behavior. Journal of Broadcasting & Electronic Media, 58(4), 634–654. https://doi.org/10.1080/08838151.2014.966363 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  269. Caren, N., Andrews, K. T., & Lu, T. (2020). Contemporary social movements in a hybrid media environment. Annual Review of Sociology, 46(1), 443–465. https://doi.org/10.1146/annurev-soc-121919-054627 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  270. Dablander, F., Wimmer, S., & Haslbeck, J. (2025). Media coverage of climate activist groups in Germany. Climatic Change, 178(8), 1–46. https://doi.org/10.1007/s10584-025-03959-8 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  271. Danner, H., Hagerer, G., Pan, Y., & Groh, G. (2022). The news media and its audience: Agenda setting on organic food in the United States and Germany. Journal of Cleaner Production, 354. https://doi.org/10.1016/j.jclepro.2022.131503 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  272. Djerf-Pierre, M., & Shehata, A. (2017). Still an agenda setter: Traditional news media and public opinion during the transition from low to high choice media environments. Journal of Communication, 67(5), 733–757. https://doi.org/10.1111/jcom.12327 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  273. Doherty, B. (2013). Tactics. In D. A. Snow, D. della Porta, B. Klandermans, & D. McAdam (Eds.), The Wiley-Blackwell Encyclopedia of Social and Political Movements. Wiley. https://doi.org/10.1002/9780470674871.wbespm210 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  274. Eilders, C. (2006). News factors and news decisions. Theoretical and methodological advances in Germany. Communications, 31(1), 5–24. https://doi.org/10.1515/COMMUN.2006.002 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  275. eurotopics. (n.d.). Media. eurotopics. https://www.eurotopics.net/en/142186/media Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  276. Evans, E. M. (2016). Bearing witness: How controversial organizations get the media coverage they want. Social Movement Studies, 15(1), 41–59. https://doi.org/10.1080/14742837.2015.1060158 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  277. Feinberg, M., Willer, R., & Kovacheff, C. (2020). The activist’s dilemma: Extreme protest actions reduce popular support for social movements. Journal of Personality and Social Psychology, 119(5), 1086–1111. https://doi.org/10.1037/pspi0000230 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  278. Fretwurst, B. (2013). Intercoderreliabilität und Expertenvalidität bei Inhaltsanalysen: Erläuterungen zur Berechnung des Reliabilitätskoeffizienten Lotus mit SPSS [Intercoder reliability and expert validity in content analyses: Explanations for calculating the Lotus reliability coefficient with SPSS]. Institut für angewandte Kommunikationsforschung. https://iakom.ch/documents/6/LotusManualGer.pdf Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  279. Fridays for Future. (2024). Aktionen [Actions]. https://fridaysforfuture.de/aktionen/ Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  280. Goldenbaum, M., & Thompson, C. S. (2020). Fridays for Future im Spiegel der Medienöffentlichkeit [Fridays for Future as reflected in the media]. In S. Haunss & M. Sommer (Eds.), Fridays for Future – Die Jugend gegen den Klimawandel (pp. 181–204). transcript. https://doi.org/10.1515/9783839453476-009 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  281. Gruber, J. B. (2023). Troublemakers in the streets? A framing analysis of newspaper coverage of protests in the UK 1992–2017. The International Journal of Press/Politics, 28(2), 414–433. https://doi.org/10.1177/19401612221102058 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  282. Haßler, J. (2017). Mediatisierung der Klimapolitik [Mediatization of climate policy]. Springer VS. https://doi.org/10.1007/978-3-658-15668-8 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  283. Heide, J. (2025). Polarizing social figures? Climate activists in German media and popular discourse. European Societies, 27(5), 959–991. https://doi.org/10.1162/euso_a_00030 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  284. Hoppe, I., Lörcher, I., & Kießling, B. (2019). Und die Welt schaut (wieder) hin? Agenda-Setting-Effekte klimabezogener Ereignisse in zwei Online-Öffentlichkeitsarenen [And the world is watching (again)? Agenda-setting effects of climate-related events in two online public arenas]. In I. Neverla, M. Taddicken, I. Lörcher, & I. Hoppe (Eds.), Klimawandel im Kopf: Studien zur Wirkung, Aneignung und Online-Kommunikation (pp. 203–228). Springer Fachmedien. https://doi.org/10.1007/978-3-658-22145-4_8 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  285. Hunt, K., & Gruszczynski, M. (2021). The influence of new and traditional media coverage on public attention to social movements: The case of the Dakota Access Pipeline protests. Information, Communication & Society, 24(7), 1024–1040. https://doi.org/10.1080/1369118X.2019.1670228 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  286. Jennings, W., & Saunders, C. (2019). Street demonstrations and the media agenda: An analysis of the dynamics of protest agenda setting. Comparative Political Studies, 52(13–14), 2283–2313. https://doi.org/10.1177/0010414019830736 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  287. Kalogeropoulos, A., Negredo, S., Picone, I., & Nielsen, R. K. (2017). Who shares and comments on news?: A cross-national comparative analysis of online and social media participation. Social Media + Society, 3(4), 1–12. https://doi.org/10.1177/2056305117735754 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  288. Kiousis, S. (2004). Explicating media salience: A factor analysis of New York Times issue coverage during the 2000 U.S. presidential election. Journal of Communication, 54(1), 71–87. https://doi.org/10.1111/j.1460-2466.2004.tb02614.x Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  289. Kleut, J., & Milojevic, A. (2021). Framing protest in online news and readers’ comments: The case of Serbian protest “Against Dictatorship”. International Journal of Communication, 15, 82–102. Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  290. Koltsova, O., & Nagornyy, O. (2019). Redefining media agendas: Topic problematization in online reader comments. Media and Communication, 7(3), 145–156. https://doi.org/10.17645/mac.v7i3.1894 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  291. Kroon, A., Welbers, K., Trilling, D., & van Atteveldt, W. (2024). Advancing automated content analysis for a new era of media effects research: The key role of transfer learning. Communication Methods and Measures, 18(2), 142–162. https://doi.org/10.1080/19312458.2023.2261372 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  292. Kumkar, N. C. (2022, November 16). Die Radikalisierung der Radikalisierungsbehauptung: Zum Diskurs über die Letzte Generation [The radicalization of the radicalization claim: On the discourse about the Last Generation]. Soziopolis: Gesellschaft beobachten. https://www.soziopolis.de/die-radikalisierung-der-radikalisierungsbehauptung.html Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  293. Küstner, K. (2023, March 15). “Letzte Generation” bisher “nicht extremistisch” [“Last Generation” so far “not extremist”]. tagesschau. Retrieved from https://www.tagesschau.de/inland/haldenwang-verfassungsschutz-letzte-generation-101.html Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  294. Langer, A. I., & Gruber, J. B. (2021). Political agenda setting in the hybrid media system: Why legacy media still matter a great deal. The International Journal of Press/Politics, 26(2), 313–340. https://doi.org/10.1177/1940161220925023 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  295. Lee, F. L. F. (2014). Triggering the protest paradigm: Examining factors affecting news coverage of protests. International Journal of Communication, 8, 2725–2746. Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  296. Letzte Generation. (2024). Gesellschaftsrat + Fragen & Antworten [Citizens’ council + questions & answers]. https://letztegeneration.org/gesellschaftsrat/ Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  297. Lörcher, I., & Taddicken, M. (2017). Discussing climate change online. Topics and perceptions in online climate change communication in different online public arenas. Journal of Science Communication, 16(2). https://doi.org/10.22323/2.16020203 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  298. Marg, S. (2024). Kurzstudie: Die Letzte Generation. Entwicklung, Merkmale und Einordung (Stand Februar 2024) [Brief study: The Last Generation. Development, characteristics and classification (as of February 2024)]. Institut für Demokratieforschung – Bundesfachstelle Linke Militanz. https://www.linke-militanz.de/data/akten/2024/03/kurzstudie-die-letzte-generation-marg-2024.pdf Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  299. McCluskey, M. R. (2008). Activist group attributes and their influences on news portrayal. Journalism & Mass Communication Quarterly, 85(4), 769–784. https://doi.org/10.1177/107769900808500404 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  300. McCombs, M. (2005). A look at agenda-setting: Past, present and future. Journalism Studies, 6(4), 543–557. https://doi.org/10.1080/14616700500250438 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  301. McCombs, M. E., & Shaw, D. L. (1972). The agenda-setting function of mass media. Public Opinion Quarterly, 36(2), 176–187. https://doi.org/10.1086/267990 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  302. McCurdy, P. (2012). Social movements, protest and mainstream media. Sociology Compass, 6(3), 244–255. https://doi.org/10.1111/j.1751-9020.2011.00448.x Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  303. McLeod, D. M. (2007). News coverage and social protest: How the media’s protest paradigm exacerbates social conflict. Journal of Dispute Resolution, 1, 185–194. Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  304. Meyer, H., Farjam, M., Rauxloh, H., & Brüggemann, M. (2025). From disruptive protests to disrupted news frames: Comparing German news on climate protests. Journalism. Advance online publication. https://doi.org/10.1177/14648849251372805 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  305. Meyer, H., Pröschel, L., & Brüggemann, M. (2025). From disruptive protests to disrupted networks? Analyzing levels of polarization in the German Twitter/X debates on “Fridays for Future” and “Letzte Generation”. Social Media + Society, 11(2), 1–16. https://doi.org/10.1177/20563051251337400 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  306. Mirowsky, J., & Ross, C. E. (1981). Protest group success: The impact of group characteristics, social control, and context. Sociological Focus, 14(3), 177–192. https://doi.org/10.1080/00380237.1981.10570394 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  307. Molter, N. (2023, May 29). Acht von zehn Deutschen: „Letzte Generation“ tut Klimaschutz keinen Gefallen [Eight out of ten Germans: “Last Generation” is not doing climate protection any favors]. Augsburger Allgemeine. Retrieved from https://www.augsburger-allgemeine.de/special/bayern-monitor/umfrage-acht-von-zehn-deutschen-letzte-generation-tut-klimaschutz-keinen-gefallen-id66635936.html Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  308. Nardini, G., Rank-Christman, T., Bublitz, M. G., Cross, S. N. N., & Peracchio, L. A. (2021). Together we rise: How social movements succeed. Journal of Consumer Psychology, 31(1), 112–145. https://doi.org/10.1002/jcpy.1201 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  309. Nepstad, S. E., & Bob, C. (2006). When do leaders matter? Hypotheses on leadership dynamics in social movements. Mobilization: An International Quarterly, 11(1), 1–22. https://doi.org/10.17813/maiq.11.1.013313600164m727 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  310. Rasmussen, A., Mäder, L. K., & Reher, S. (2018). With a little help from the people? The role of public opinion in advocacy success. Comparative Political Studies, 51(2), 139–164. https://doi.org/10.1177/0010414017695334 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  311. Roberts, M., Wanta, W., & Dzwo, T.-H. (D.). (2002). Agenda setting and issue salience online. Communication Research, 29(4), 452–465. https://doi.org/10.1177/0093650202029004004 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  312. Rucht, D. (2012). Massen mobilisieren [Mobilize the masses]. APuZ, 62(25–26), 3–9. Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  313. Rucht, D. (2023). Die Letzte Generation: Beschreibung und Kritik [The Last Generation: Description and review] (ipb working series 1/2023). ipb. https://protestinstitut.eu/wp-content/uploads/2023/04/WP_1.2023.pdf Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  314. Scheu, A. M. (2019). Between offensive and defensive mediatization. An exploration of mediatization strategies of German science-policy stakeholders. Journal of Science Communication, 18(3). https://doi.org/10.22323/2.18030208 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  315. Shuman, E., Goldenberg, A., Saguy, T., Halperin, E., & van Zomeren, M. (2024). When are social protests effective? Trends in Cognitive Sciences, 28(3), 252–263. https://doi.org/10.1016/j.tics.2023.10.003 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  316. Smidt, C. D. (2012). Not all news is the same: Protests, presidents, and the mass public agenda. Public Opinion Quarterly, 76(1), 72–94. https://doi.org/10.1093/poq/nfr019 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  317. Smith, J., McCarthy, J. D., McPhail, C., & Augustyn, B. (2001). From protest to agenda building: Description bias in media coverage of protest events in Washington, D.C. Social Forces, 79(4), 1397–1423. https://doi.org/10.1353/sof.2001.0053 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  318. Strehler-Schaaf, M. (2025). Proteste für Zeitungen, Fernsehen und Insta? Wie sich Protestbewegungen (nicht) an wahrgenommene Medienlogiken anpassen [Protests for newspapers, television, and Instagram? How protest movements (do not) adapt to perceived media logic]. Springer VS. https://doi.org/10.1007/978-3-658-49959-4 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  319. Strömbäck, J., & Esser, F. (2017). Political public relations and mediatization: The strategies of news management. In P. Van Aelst & S. Walgrave (Eds.), How Political Actors Use the Media: A Functional Analysis of the Media’s Role in Politics (pp. 63–83). Palgrave Macmillan. https://doi.org/10.1007/978-3-319-60249-3_4 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  320. Strömbäck, J., & Van Aelst, P. (2013). Why political parties adapt to the media: Exploring the fourth dimension of mediatization. International Communication Gazette, 75(4), 341–358. https://doi.org/10.1177/1748048513482266 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  321. SWR Aktuell. (2023, July 17). Aktiver Widerstand. Finanzierung, Ziele, Hintergründe: Das ist die “Letzte Generation” [Active resistance. Financing, goals, background: This is the “Last Generation”]. SWR Aktuell. Retrieved from https://web.archive.org/web/20250319025721/https://www.swr.de/swraktuell/letzte-generation-klimaaktivisten-fragen-antworten-100.html Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  322. Thomas-Walters, L., Scheuch, E. G., Ong, A., & Goldberg, M. H. (2025). The impacts of climate activism. Current Opinion in Behavioral Sciences, 63. https://doi.org/10.1016/j.cobeha.2025.101498 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  323. Thoms, C. (2023). Im Sinne der Medien – Textverständlichkeit im Nachrichtenauswahlkontext [Serving media preferences – text comprehensibility in the news selection context]. Springer VS. https://doi.org/10.1007/978-3-658-40007-1 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  324. Tilly, C., & Tarrow, S. (2015). Contentious politics. Oxford University Press. Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  325. Van Aelst, P., Thesen, G., Walgrave, S., & Vliegenthart, R. (2014). Mediatization and political agenda-setting: Changing issue priorities? In F. Esser & J. Strömbäck (Eds.), Mediatization of Politics: Understanding the Transformation of Western Democracies (pp. 200–220). Palgrave Macmillan. https://doi.org/10.1057/9781137275844_11 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  326. Vliegenthart, R., & Walgrave, S. (2012). The interdependency of mass media and social movements. In H. A. Semetko & M. Scammell (Eds.), The SAGE Handbook of Political Communication (pp. 387–397). SAGE. https://doi.org/10.4135/9781446201015.n31 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  327. Waddell, T. F. (2018). What does the crowd think? How online comments and popularity metrics affect news credibility and issue importance. New Media & Society, 20(8), 3068–3083. https://doi.org/10.1177/1461444817742905 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  328. Wallace, S. J., Zepeda-Millán, C., & Jones-Correa, M. (2014). Spatial and temporal proximity: Examining the effects of protests on political attitudes. American Journal of Political Science, 58(2), 433–448. https://doi.org/10.1111/ajps.12060 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  329. Walter, S., Brüggemann, M., & Engesser, S. (2018). Echo chambers of denial: Explaining user comments on climate change. Environmental Communication, 12(2), 204–217. https://doi.org/10.1080/17524032.2017.1394893 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  330. Wouters, R., & Lefevere, J. (2023). Making their mark? How protest sparks, surfs, and sustains media issue attention. Political Communication, 40(5), 615–632. https://doi.org/10.1080/10584609.2023.2188499 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  331. Wouters, R., & Van Camp, K. (2017). Less than expected? How media cover demonstration turnout. The International Journal of Press/Politics, 22(4), 450–470. https://doi.org/10.1177/1940161217720773 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  332. Zlobina, A., & Gonzalez Vazquez, A. (2018). What is the right way to protest? On the process of justification of protest, and its relationship to the propensity to participate in different types of protest. Social Movement Studies, 17(2), 234–250. https://doi.org/10.1080/14742837.2017.1393408 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-015
  333. Apitzsch, B. (2017). Zwischen Traumberuf und ungewisser Zukunft: Projektarbeitsmärkte in der Film- und Fernsehindustrie. [Between a dream job and an uncertain future: project-based work in the film and television industry.] KM Magazin, 119(119), 34–37. Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  334. Apitzsch, B., & Piotti, G. (2012). Institutions and sectoral logics in creative industries: The media cluster in Cologne. Environment and Planning A: Economy and Space, 44(4), 921–936. https://doi.org/10.1068/a44285 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  335. Aylett, H., Raveney, F., Gore, T., & Prommer, E. (2016). Where are all the women directors? Report on gender equality for directors in the European film industry. EWA Women directors in film – Comparative report. European Women’s Audiovisual Network (EWA). https://www.ewawomen.com/wp-content/uploads/2018/09/Complete-report_compressed.pdf Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  336. Banks, M. (2009). Gender below-the-line: Defining feminist production studies. In V. Mayer, M. J. Banks, & J. T. Caldwell (Eds.), Production studies: Cultural studies of media industries (pp. 87–98). Routledge. Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  337. Banks, M. (2019). Film schools as pre-industry: Fostering creative collaboration and equity in media production programs. Media Industries Journal, 6(1). https://doi.org/10.3998/mij.15031809.0006.105 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  338. Bastian, M., Heymann, S., & Jacomy, M. (2009). Gephi: An open source software for exploring and manipulating networks. https://doi.org/10.1609/icwsm.v3i1.13937 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  339. Bathelt, H., & Gräf, A. (2008). Internal and external dynamics of the Munich film and TV industry cluster, and limitations to future growth. Environment and Planning A: Economy and Space, 40(8), 1944–1965. https://doi.org/10.1068/a39391 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  340. Berauer, W. (2017). Filmstatistisches Jahrbuch 2016. [Film Statistics Yearbook 2016] Nomos. Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  341. BFI. (2026). BFI diversity standards. https://www.bfi.org.uk/inclusion-film-industry/bfi-diversity-standards Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  342. Blair, H. (2001). ‘You’re only as good as your last job’: The labour process and labour market in the British film industry. Work, Employment and Society, 15(1), 149–169. https://doi.org/10.1177/09500170122118814 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  343. Cobb, S. (2019). What about the men? Gender inequality data and the rhetoric of inclusion in the US and UK film industries. Journal of British Cinema and Television, 17(1), 112–135. https://doi.org/10.3366/jbctv.2020.0510 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  344. Conor, B. (2021). Gender & creativity: Progress on the precipice. UNESCO. https://doi.org/10.58337/TTGU8976 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  345. Dadlani, A., Vo, V., Khemka, A., Harvey, S. T., Kantoro Kyzy, A., Jones, P., & Verhoeven, D. (2024). Leading by the nodes: A survey of film industry network analysis and datasets. Applied Network Science, 9(1). https://doi.org/10.1007/s41109-024-00673-9 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  346. Decker-Tonnesen, P. L., Chesak, S. S., Walker, L. E., Kohler, K., Phelan, S., Gunnels, M. S., Saliba, K. L., & Bhagra, A. (2025). Role of organizational network analyses to advance workforce inclusion and belonging: A scoping literature review. Frontiers in Psychology, 16. https://doi.org/10.3389/fpsyg.2025.1708522 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  347. Deutscher Kulturrat. (2020, July 15). Mentoringprogramm für weibliche Führungskräfte im Kulturbereich: Start der 4. Runde. [Mentoring programme for female leaders in the cultural sector: Launch of the fourth round.] Retrieved from https://www.kulturrat.de/presse/pressemitteilung/mentoringprogramm-4-runde/ Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  348. Du Toit, S. H. C., Steyn, A. G. W., & Stumpf, R. H. (1986). Graphical exploratory data analysis. Springer New York. https://doi.org/10.1007/978-1-4612-4950-4 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  349. Faulkner, R. R., & Anderson, A. B. (1987). Short-term projects and emergent careers: Evidence from Hollywood. American Journal of Sociology, 92(4), 879–909. https://doi.org/10.1086/228586 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  350. FFA. (2016). Geschäftsbericht 2015 [Annual Report 2015]. Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  351. FFA. (2021). Geschäftsbericht 2020 [Annual Report 2020]. Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  352. FFA. (2022). Fokus Gender. FFA Filmförderungsanstalt. https://www.ffa.de/gender.html Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  353. FFA. (2025). Das Kinojahr 2024: Kino- und Filmergebnisse/Filmförderung in Zahlen. Deutscher Film. [The Cinema Year 2024: Cinema and Film Results/Film Funding in Figures. German Film.] Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  354. Filmuniversität Babelsberg Konrad Wolf, Deutsche Film- und Fernsehakademie Berlin, Filmakademie Baden-Württemberg, Hochschule für Fernsehen und Film München, Internationale Filmschule Köln & Kunsthochschule für Medien Köln (2018). Together for gender equality. https://rm.coe.int/together-for-gender-equality/168091d93e Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  355. Flicker, E., & Vogelmann, L. L. (2018). Österreichischer Film Gender Report 2012–2016: Zentrale Ergebnisse. [Austrian film gender report 2012–2016: Key findings] https://filminstitut.at/wp-content/uploads/2023/12/OesterreichischerFilmGenderReport2012-2016.pdf Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  356. Goodfellow, M. (2018, September 21). France launches gender parity production incentives. Screen Daily. Retrieved from https://www.screendaily.com/news/france-launches-gender-parity-production-incentives/5132855.article Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  357. Grimme, F., Wittner, B., & Kauffeld, S. (2026). Networking and career success: Analysing social capital in formal female networks. Journal of Management Development, 45(2), 226–248. https://doi.org/10.1108/JMD-01-2025-0017 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  358. Hochfeld, K., Genz, K., Iffländer, V., & Prommer, E. (2017). Gender und Film: Rahmenbedingungen und Ursachen der Geschlechterverteilung von Filmschaffenden in Schlüsselpositionen in Deutschland. [Gender and Film: Context and causes of gender distribution among film professionals in key positions in Germany.] FFA-Filmförderungsanstalt. https://www.ffa.de/files/ffa/gender/Studie percent20GENDER percent20UND percent20FILM.pdf Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  359. hooks, b. (2015). Black looks: Race and representation. Routledge. Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  360. Hoyler, M., & Watson, A. (2018). Framing city networks through temporary projects: (Trans)national film production beyond ‘Global Hollywood’. Urban Studies, 56(5), 943–959. https://doi.org/10.1177/0042098018790735 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  361. IHK München (2026, January 9). Medien. Retrieved from https://www.ihk-muenchen.de/politik/interessenvertretung/medien/ Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  362. Jones, C. (1996). Careers in project networks: The case of the film industry. In M. B. Arthur (Ed.), The boundaryless career: A new employment principle for a new organizational era (pp. 58–75). Oxford University Press. Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  363. Jones, P., Verhoeven, D., Dadlani, A., & Zemaityte, V. (2024). She must be seeing things! Gender disparity in camera department networks. Social Networks, 76, 120–134. https://doi.org/10.1016/j.socnet.2023.09.004 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  364. Jones, P., Verhoeven, D., & Espinosa-Rada, A. (2026). The role of film school collaboration in film industry network formation: An empirical analysis of data from the Australian Film, Television and Radio School (AFTRS). Journal of Cultural Analytics. Advance online publication. https://doi.org/10.22148/jca.1173 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  365. Kaiser, R., & Liecke, M. (2007). The Munich feature film cluster: The degree of global integration and explanations for its relative success. Industry & Innovation, 14(4), 385–399. https://doi.org/10.1080/13662710701524031 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  366. Kanzler, M. (2021). Fiction film financing in Europe: A sample analysis of films released in 2019. https://rm.coe.int/fiction-film-financing-in-europe-2021-edition/1680a57229 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  367. Kearney, M., & Twenty Female Film Students. (2018). Melting the celluloid ceiling: Training girl filmmakers, revolutionizing media culture. In M. G. Blue & M. C. Kearney (Eds.) Mediated girlhoods (pp. 213–232). Peter Lang. Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  368. Krätke, S. (2002). Network analysis of production clusters: The Potsdam/Babelsberg film industry as an example. European Planning Studies, 10(1), 27–54. https://doi.org/10.1080/09654310120099254 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  369. Langer, J. (2019). GENDER.DOK Untersuchung zur Genderverteilung im Bereich Regie bei Reportagen, Dokumentationen und Kinodokumentarfilmen. [GENDER.DOK Study on gender distribution in directing roles for news reports, documentaries and feature-length documentaries.] https://media02.culturebase.org/data/docs-ag-dok/GENDER.DOK.pdf Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  370. Lauzen, M. M. (2021). The Celluloid ceiling report: Behind-the-scenes employment of women on the top U.S. films of 2020. https://womenintvfilm.sdsu.edu/wp-content/uploads/2021/01/2020_Celluloid_Ceiling_Report.pdf Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  371. Liddy, S. (2020). Women in the international film industry: Policy, practice and power. Palgrave Macmillan. Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  372. Linke, C., & Prommer, E. (2021). From fade-out into spotlight: An audio-visual character analysis (ACIS) on the diversity of media representation and production culture. Studies in Communication Sciences, 21(1), 145–161. https://doi.org/10.24434/j.scoms.2021.01.010 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  373. Loist, S. (2018). Gendered media industries: Argumente für eine geschlechtergerechte und diverse Filmindustrie. [Gendered media industries: Arguments for a gender-equal and diverse film industry.] Navigationen, 18(2), 135–158. Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  374. Loist, S., & Prommer, E. (2019). Gendered production culture in the German film industry. Media Industries Journal, 6(1). https://doi.org/10.3998/mij.15031809.0006.106 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  375. Loist, S., Verhoeven, D., Eikhof, D. R., Prommer, E., Ehrich, M. E., Jones, P., Guyan, K., Coles, A., Radziwill, S., & Dadlani, A. (2024). Re-framing the picture: An international comparative assessment of gender equity policies in the film sector. https://doi.org/10.60529/390 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  376. Lutter, M. (2015). Do women suffer from network closure? The moderating effect of social capital on gender inequality in a project-based labor market, 1929 to 2010. American Sociological Review, 80(2), 329–358. https://doi.org/10.1177/0003122414568788 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  377. Maier, T., Amtsberg, L. B., & Radziwill, S. (2024). Achter Regie-Diversitätsbericht des Bundesverbandes Regie e.V. (BVR) für die Jahre 2022 und 2023: Genderanalyse zur Regievergabepraxis in deutschen fiktionalen Primetime-Programmen von ARD, ZDF, RTL, SAT.1, Pro7 und VOX sowie der Streaminganbieter und im deutschen Kinospielfilm. [Eighth Diversity Report on Directing by the Bundesverband Regie e.V. (BVR) for the years 2022 and 2023: Gender analysis of directing commissioning practices in German primetime fiction programmes on ARD, ZDF, RTL, SAT.1, Pro7 and VOX, as well as among streaming providers and in German feature films] Bundesverband Regie e.V., Berlin. Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  378. Martin, S., Brown, W. M., Klavans, R., & Boyack, K. W. (2011). OpenOrd: An open-source toolbox for large graph layout. https://doi.org/10.1117/12.871402 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  379. McPherson, M., & Smith-Lovin, L. (1993). You are who you know: A network perspective on gender. In P. England (Ed.), Theory on gender/feminism on theory (pp. 223–241). Aldine. Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  380. Medienboard Berlin Brandenburg (2021). MBB Tätigkeitsbericht 2020. [MBB Annual Report 2020] https://www.medienboard.de/fileadmin/user_upload/pdf/Publikationen/MBB_Taetigkeitsbericht_2020.pdf Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  381. MOIN Filmförderung Hamburg Schleswig-Holstein. (2020). Diversity Checklist der MOIN Filmförderung [Diversity Checklist of the MOIN Film Fund]. https://www.moin-filmfoerderung.de/de/ueber_die_filmfoerderung/diversity-checklist-filmfoerderung.php Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  382. Mossig, I. (2006). Netzwerke der Kulturökonomie: Lokale Knoten und globale Verflechtungen der Film- und Fernsehindustrie in Deutschland und den USA. [Networks in the cultural economy: Local hubs and global interconnections in the film and television industry in Germany and the USA.] transcript. Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  383. Mulvey, L. (1975). Visual pleasure and narrative cinema. Screen, 16(3), 6–18. https://doi.org/10.1093/screen/16.3.6 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  384. New Inclusion. (2022). Review of the BFI Diversity Standards: A Summary of Industry Perspectives & Recommendations. BFI. https://core-cms.bfi.org.uk/media/16482/download Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  385. Ng, A., & Soo, K. (2018). Data Science – Was ist das eigentlich?! Algorithmen des maschinellen Lernens verständlich erklärt. [Data science – What is it, anyway?! Machine-learning algorithms explained in simple terms] Springer. https://doi.org/10.1007/978-3-662-56776-0 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  386. Österreichisches Filminstitut. (2019). Gender incentive. https://filminstitut.at/foerderung/gender-incentive Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  387. Prommer, E., & Görland, S. O. (2022). Methodische Herausforderungen von Data-Mining, Autocoding und sozialer Netzwerkanalyse: Das Beispiel des Gender-Gaps in der Filmproduktion in Deutschland. [Methodological challenges of data mining, autocoding and social network analysis: The example of the gender gap in film production in Germany.] In C. Lohmeier & T. Wiedemann (Eds.), Datenvielfalt in kommunikationswissenschaftlichen Forschungskontexten (pp. 105–125). Springer VS. https://doi.org/10.1007/978-3-658-36645-2_6 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  388. Prommer, E., & Loist, S. (2020). Where are the female creatives? The status quo of the German screen industry. In S. Liddy (Ed.), Women in the international film industry: Policy, practice and power (pp. 43–60). Palgrave Macmillan. https://doi.org/10.1007/978-3-030-39070-9_3 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  389. Prommer, E., & Loist, S. (2026). Film industry: Production culture with gender bias. In J. Dorer, B. Geiger, B. Hipfl, & V. Ratković (Eds.), Handbook of media and gender: Perspectives and findings of feminist communication and media studies (pp. 499–511). Palgrave Macmillan. https://doi.org/10.1007/978-3-658-45789-1_38 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  390. Prommer, E., & Siegemund, S. (2022). Siebter Regie-Diversitätsbericht des Bundesverbandes Regie e.V. (BVR) für die Jahre 2019 und 2020. Genderanalyse zur Regievergabepraxis in deutschen fiktionalen Primetime-Programmen von ARD, ZDF, RTL, SAT.1, Pro7 und VOX sowie der Streaminganbieter und im deutschen Kinospielfilm. Im Auftrag des Bundesverbandes Regie e.V. [Seventh Diversity Report on Directing by the Bundesverband Regie e.V. (BVR) for the years 2019 and 2020. Gender analysis of directing commissioning practices in German primetime fiction programmes on ARD, ZDF, RTL, SAT.1, Pro7 and VOX, as well as among streaming providers and in German feature films] Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  391. Ross, K., & Padovani, C. (Eds.). (2017). Gender Equality and the Media: A Challenge for Europe. Routledge. Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  392. Screen Australia. (2015). Gender matters: Women in the Australian screen industry. Screen Australia. https://www.agec.org.au/wp-content/uploads/2018/09/Gender-Matters-Women-in-the-Australian-Screen-Industry-2017.pdf Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  393. Simone, P. (2024). Female professionals in European film production: 2023 edition. https://rm.coe.int/female-professionals-in-european-film-production-eao-report/1680ad13c5 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  394. Smith, S. L., Choueiti, M., Pieper, K., Case, A., Yao, K., & Vranich, E. (2020). Inequality in 1,300 popular films: Examining portrayals of gender, race/ethnicity, LGBTQ & disability from 2007 to 2019. USC Annenberg Inclusion Initiative. Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  395. Smith, S. L., Choueiti, M., Yao, K., Clark, H., & Pieper, K. M. (2020). Inclusion in the director’s chair: Analysis of director gender & race/ethnicity across 1,300 top films from 2007 to 2019. USC Annenberg Inclusion Initiative. http://assets.uscannenberg.org/docs/aii-inclusion-directors-chair-20200102.pdf Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  396. Steinbauer, A. (2019, March 4). Weiblicher, jünger, erfolgreicher. [More feminine, younger, more successful.] Süddeutsche Zeitung. Retrieved from https://www.sueddeutsche.de/medien/zdf-weiblicher-juenger-erfolgreicher-1.4353999 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  397. Swedish Film Institute. (2018). The money issue: Gender equality report 2018. https://www.filminstitutet.se/globalassets/2.-fa-kunskap-om-film/analys-och-statistik/publications/other-publications/sfi-gender-equality-report-2018---lowres.pdf Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  398. Sydow, J., & Windeler, A. (2006). Neue Organisationsformen in der Medienökonomie. [New forms of organisation in the media industry.] In K.-D. Altmeppen & M. Karmasin (Eds.), Medien und Ökonomie: Band 3: Anwendungsfelder der Medienökonomie (pp. 47–60). VS Verlag für Sozialwissenschaften. https://doi.org/10.1007/978-3-531-90195-4_3 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  399. Sydow, J., Windeler, A., & Wirth, C. (2002). Markteintritt als kollektiver Netzwerkeintritt: Internationalisierung der Fernsehproduktion in unreife Märkte. [Market entry as collective network entry: The internationalisation of television production in immature markets.] Betriebswirtschaft, 62(5), 459–473. Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  400. UFA. (2020). Diversity. https://www.ufa.de/die-ufa/verantwortung/diversity Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  401. Verhoeven, D. (2017). The “Gender Offender” analysis: How and why we did it (Part two) | Kinomatics. https://kinomatics.com/posts/the-gender-offender-analysis-how-and-why-we-did-it-part-two/ Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  402. Verhoeven, D. (2024, August 26). Beyond ‘one and done’: Achieving gender equity in the film industry depends on more than entry programs. The Conversation. Retrieved from https://theconversation.com/beyond-one-and-done-achieving-gender-equity-in-the-film-industry-depends-on-more-than-entry-programs-232553 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  403. Verhoeven, D., Musial, K., Palmer, S., Taylor, S., Abidi, S., Zemaityte, V., & Simpson, L. (2020). Controlling for openness in the male-dominated collaborative networks of the global film industry. PLOS ONE, 15(6). https://doi.org/10.1371/journal.pone.0234460 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  404. Verhoeven, D., & Palmer, S. (2016, November 15). Women aren’t the problem in the film industry, men are. The Conversation. Retrieved from http://theconversation.com/women-arent-the-problem-in-the-film-industry-men-are-68740 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  405. Windeler, A. (2004). Organisation der TV-Produktion in Projektnetzwerken: Zur Bedeutung von Produkt- und Industriespezifika. [Organising TV production in project networks: The importance of product and industry-specific factors.] In J. Sydow & A. Windeler (Eds.), Organisation der Content-Produktion (pp. 55–76). VS Verlag für Sozialwissenschaften. https://doi.org/10.1007/978-3-322-80413-6_4 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  406. Windeler, A., Lutz, A., & Wirth, C. (2001). Netzwerksteuerung durch Selektion: Die Produktion von Fernsehserien in Projektnetzwerken. [Network control through selection: The production of television series in project networks.] Montage AV, 10(1), 91–124. https://doi.org/10.25969/mediarep/94 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  407. Women in Film & Television UK. (2026). Mentoring. https://www.wftv.org.uk/mentoring Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  408. Worschech, R. (2024, April 26). Filmförderung: Noch viel zu tun. [Film funding: There is still a lot to be done.] Epd Film. Retrieved from https://www.epd-film.de/meldungen/2024/filmfoerderung-noch-viel-zu-tun Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016
  409. Wreyford, N. (2015). Birds of a feather: Informal recruitment practices and gendered outcomes for screenwriting work in the UK film industry. The Sociological Review, 63, 84–96. https://doi.org/10.1111/1467-954X.12242 Open Google Scholar DOI: 10.5771/2192-4007-2026-3-016

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