Bilim İletişimi ve Yapay Zekâ: Kavramsal Dönüşümler ve Tematik Eğilimler Çerçevesinde Bir Analiz

Öz

Bu çalışma, yapay zekânın bilim iletişimi literatüründe nasıl kavramsallaştırıldığını ve hangi tematik yönelimler etrafında tartışıldığını incelemektedir. Bu doğrultuda çalışmada, Web of Science veri tabanında "iletişim" konu kategorisinde yer alan, Q1 ve Q2 çeyreklik dilimlerinde sınıflandırılmış ve kapsamı bilim iletişimi olan Science Communication, Journal of Science Communication ve Public Understanding of Science isimli üç dergide yayımlanmış yapay zekâ temalı çalışmalar, tematik analiz yoluyla incelenmiştir. Analiz sonucunda, yapay zekânın sosyoteknik bir fenomen ve iletişimsel süreçlerini dönüştüren bir araç olarak, güven, risk ve etik bağlamlarda kavramsallaştırıldığı; yapay zekânın toplumsal algı ve kabul gibi süreçlerdeki konumunun medya çerçeveleri ve temsilleri üzerinden ele alındığı; yapay zekâ teknolojilerinin bilim iletişimine entegrasyonunun dijital bilim iletişimi araştırmaları etrafında şekillendiği görülmüştür. Ayrıca, bulgular doğrultusunda elde edilen araştırma gündemi üzerinden gelecek araştırmalara yönelik öneriler sunulmuştur.

Anahtar Kelimeler

• Bilim iletişimi
• yapay zekâ
• iletişimsel yapay zekâ
• dijital bilim iletişimi

Science Communication and Artificial Intelligence: An Analysis of Conceptual Transformations and Thematic Trends

Öz

This study explores how artificial intelligence (AI) is conceptualized and thematically discussed in science communication research. Using thematic analysis, AI-related articles published in Science Communication, Journal of Science Communication, and Public Understanding of Science—leading journals ranked in Q1–Q2 under the “Communication” category in the Web of Science—were examined. The findings show that AI is viewed both as a sociotechnical phenomenon and as a tool transforming communication processes, especially regarding trust, risk, and ethics. The role of AI in shaping public perception and acceptance is analyzed through media framings and representations, while its integration into science communication is positioned within digital science communication research. Besides the study offers recommendations for future researchs based on the research agenda in line with the findings.

Anahtar Kelimeler

• science communication
• artificial intelligence
• communicative artificial intelligence
• digital science communication

Kaynakça

1. AA. (2025), YÖK Başkanı Özvar: Yükseköğretim Kurulu Bilim İletişimi Ofisini Hayata Geçiriyoruz. https://www.aa.com.tr/tr/egitim/yok-baskani-ozvar-yuksekogretim-kurulu-bilim-iletisimi-ofisini-hayata-geciriyoruz/3484456 (Erişim Tarihi: 05.08.2025).
2. Akin, H. (2017), Overview of the Science of Science Communication. (Eds.: K. H. Jamieson), The Oxford Handbook of the Science of Science Communication, s. 24-33, New York: Oxford University Press.
3. Alvarez, A., Caliskan, A., Crockett, M.J., Ho, S. S., Messeri, L. & West, J. (2024), Science Communication with Generative AI. Nature Human Behaviour, 8, s. 625–627.
4. Baake, J., Schmitt, J. and Metag, J. (2025), Balancing Realism and Trust: AI Avatars in Science Communication. JCOM, 24(02), A03. https://doi.org/10.22323/2.24020203
5. Bauer, W. M. & Falade, A. B. (2021), Public Understanding of Science: Survey Research Around the World. (Eds.: M. Bucchi and B. Trench), Routledge Handbook of Public Communication of Science and Technology, s. 238-266. New York: Routledge.
6. Beckmann, S. A., Link, E. and Bachl, M. (2025), “ChatGPT, is the Influenza Vaccination Useful?” Comparing Perceived Argument Strength and Correctness of Pro-Vaccination-Arguments from AI and Medical Experts. JCOM, 24(02), A04. https://doi.org/10.22323/2.24020204
7. Bedir, U. (2020), Yeni Medya ve Bilim İletişimi: Türkiye’de Çevrimiçi Bilim Anlatıcılığı. (Eds:. U. Bedir). Bilim İletişimi Aktörler, Mecralar ve Sorunlar, s. 157-205), Konya: Eğitim Yayınevi.
8. Besley, C. J. & Dudo, A. (2022), Strategic Science Communication: A Guide to Setting the Right Objectives for More Effective Public Engagement. Baltimore: John Hopkins University Press.

9. Bingaman, J., Brewer, P. R., Paintsil, A., & Wilson, D. C. (2021), “Siri, Show Me Scary Images of AI”: Effects of Text-Based Frames and Visuals on Support for Artificial Intelligence. Science Communication, 43(3), s. 388-401. https://doi.org/10.1177/1075547021998069
10. Boztepe Taşkıran, H., & Ağca, M. E. (2025), Bilim İletişimi Perspektifinden Bilim İnsanlarının Sosyal Medya Kullanımı: Türkiye’nin ve Dünyanın En Etkili Bilim İnsanları Üzerine Karşılaştırmalı Bir Analiz. Intermedia International E-journal, 12(22), s. 27-50. https://doi.org/10.56133/intermedia.1527689
11. Brewer, P. R., Bingaman, J., Paintsil, A., Wilson, D. C., & Dawson, W. (2022), Media Use, Interpersonal Communication, and Attitudes Toward Artificial Intelligence. Science Communication, 44(5), s. 559-592. https://doi.org/10.1177/10755470221130307
12. Braun, V., & Clarke, V. (2006), Using Thematic Analysis in Psychology. Qualitative Research in Psychology, 3(2), s. 77–101. https://doi.org/10.1191/1478088706qp063oa
13. Braun, V., & Clarke, V. (2019), Reflecting on Reflexive Thematic Analysis. Qualitative Research in Sport, Exercise and Health, 11(4), s. 589–597. https://doi.org/10.1080/2159676X.2019.1628806
14. Braun, V., & Clarke, V. (2022), Thematic Analysis: A Practical Guide. London: Sage.
15. Brossard, D. & Scheufele, D. (2022), The Chronic Growing Pains of Communicating Science Online. Science, 375(6581), s. 613-614.
16. Bucchi, M. & Trench, B. (2021), Science Communication as the Social Conversation Around Science. (Eds.: M. Bucchi and B. Trench), Routledge Handbook of Public Communication of Science and Technology, s. 1-13. New York: Routledge.
17. Cardillo, A. (2025), 40+ Chatbot Statistics (2025). https://explodingtopics.com/blog/chatbot-statistics, (Erişim Tarihi: 03.10.2025).
18. Cave, S., Dihal, K., Drage, E., & McInerney, K. (2023), Who Makes AI? Gender and Portrayals of AI Scientists in Popular Film, 1920–2020. Public Understanding of Science, 32(6), s. 745-760. https://doi.org/10.1177/09636625231153985
19. Chan, HY., Erduran, S. (2025), How Scientists’ Narratives on AI Signal a New Era for Science Education. Research in Science Education. https://doi.org/10.1007/s11165-025-10307-4
20. Choi, S., Lee, C., Park, A., & Lee, J. A. (2024), How the Public Makes Sense of Artificial Intelligence: The Interplay Between Communication and Discrete Emotions. Science Communication, 47(4), s. 553-584. https://doi.org/10.1177/10755470241297664
21. Coletti, A., McGloin, R., Oeldorf-Hirsch, A. & Hamlin, E. (2022), Science Communication on Social Media:Examining Cross-Platform Behavioral Engagement. The Journal of Social Media in Society, 11(2), s. 236-263.
22. Daniore, P., Sedlakova, J., Zavattaro, F., Huber, Z., Knieps, M., Haulotte, M., Agbessi Alangue, T., Faulk, A., von Wyl, V., Benhamou, Y., & Gille, F. (2025), Public Views on Research with Publicly Available Data in Switzerland: Implications for Digital Research, Science Communication, and Policy. Public Understanding of Science, 0(0). https://doi.org/10.1177/09636625251330575
23. David, P., Choung, H., & Seberger, J. S. (2024), Who is Responsible? US Public Perceptions of AI Governance Through the Lenses of Trust and Ethics. Public Understanding of Science, 33(5), s. 654-672. https://doi.org/10.1177/09636625231224592
24. Davies, S. R., & Horst, M. (2016), Science Communication: Culture, Identity and Citizenship, Wiesbaden: Springer.
25. Drioli, A. (2025), The Scico+_ High Professional Skills for Advanced Science Communication Project. (Eds.: A. Drioli), Communicating Science Today: SCI-CO+ High Professional Skills for Advanced Science Communication, s. 9-13, Milano: Egea.
26. Fähnrich, B. (2021), Conceptualizing Science Communication in Flux — A Framework for Analyzing Science Communication in a Digital Media Environment JCOM, 20(03), Y02. https://doi.org/10.22323/2.20030402
27. Frank, A. L., Cacciatore, M. A., Yeo, S. K. and Su, L. Y.-F. (2025), Wit Meets Wisdom: The Relationship Between Satire and Anthropomorphic Humor on Scientists' Likability and Legitimacy. JCOM, 24(01), A04. https://doi.org/10.22323/2.24010204
28. Goh, T. J., & Ho, S. S. (2024), Trustworthiness of Policymakers, Technology Developers, and Media Organizations Involved in Introducing AI for Autonomous Vehicles: A Public Perspective. Science Communication, 46(5), s. 584-618. https://doi.org/10.1177/10755470241248169
29. Gong, Z., & Su, L. Y.-F. (2024), Exploring the Influence of Interactive and Empathetic Chatbots on Health Misinformation Correction and Vaccination Intentions. Science Communication, 47(2), s. 276-308. https://doi.org/10.1177/10755470241280986
30. Greussing, E., Guenther, L., Baram-Tsabari, A., Dabran-Zivan, S., Jonas, E., Klein-Avraham, I., Taddicken, M., Agergaard, T., Beets, B., Brossard, D., Chakraborty, A., Fage-Butler, A., Huang, C.-J., Kankaria, S., Lo, Y.-Y., Middleton, L., Nielsen, K. H., Riedlinger, M. and Song, H. (2025a), Exploring Temporal and Cross-National Patterns: The Use of Generative AI in Science-Related Information Retrieval Across Seven Countries. JCOM, 24(02), A05. https://doi.org/10.22323/2.24020205
31. Greussing, E., Guenther, L., Baram-Tsabari, A., Dabran-Zivan, S., Jonas, E., Klein-Avraham, I., Taddicken, M., Agergaard, T. E., Beets, B., Brossard, D., Chakraborty, A., Fage-Butler, A., Huang, C.-J., Kankaria, S., Lo, Y.-Y., Nielsen, K. H., Riedlinger, M., & Song, H. (2025b), The Perception and Use of Generative AI for Science-Related Information Search: Insights From A Cross-National Study. Public Understanding of Science, 34(5), s. 599-615. https://doi.org/10.1177/09636625241308493
32. Guenther, L., Kunert, J. and Goodwin, B. (2025), “Away From This Duty of Chronicler and Towards the Unicorn”: How German Science Journalists Assess Their Future with (generative) Artificial Intelligence. JCOM, 24(02), A06. https://doi.org/10.22323/2.24020206
33. Gunkel, D. J. (2012), Communication and Artificial Intelligence: Opportunities and Challenges for the 21st Century. Communication +1, 1(1). doi: https://doi.org/10.7275/R5QJ7F7R
34. Guzman, A. L. (Ed.) (2018), Human-Machine Communication. New York: Peter Lang. https://www.peterlang.com/document/1055458
35. Guzman, A. L. & Lewis, S. C. (2019), Artificial Intelligence and Communication: A Human–Machine Communication Research Agenda. New Media & Society, 22(1), s. 70–86.
36. Hara, N., Kim, E., Akter, S. and Miyazaki, K. (2025), Exploring the Dynamics of Interaction About Generative Artificial Intelligence Between Experts and the Public on Social Media. JCOM, 24(01), A02. https://doi.org/10.22323/2.24010202
37. Hendriks, F., David, B-B. Y., Banse, L., Fick, J., Greussing, E. Klein-Avraham, I., Rakedzon, T., Taddicken, M., & Baram-Tsabari, A. (2025), Generative AI in Science Communication: Fostering Scientists’ Good Working Habits for Ethical and Effective Use. Science Communication, 0(0). https://doi.org/10.1177/10755470251343486
38. Henke, J. (2024), Navigating the AI Era: University Communication Strategies and Perspectives on Generative AI Tools. JCOM, 23(03), A05. https://doi.org/10.22323/2.23030205 Henke, J. (2025), The New Normal: The Increasing Adoption of Generative AI in University Communication. JCOM, 24(02), A07. https://doi.org/10.22323/2.24020207
39. Hohenwalde, C., Leidecker-Sandmann, M., Promies, N. and Lehmkuhl, M. (2025), ChatGPT’s Potential for Quantitative Content Analysis: Categorizing Actors in German News Articles. JCOM, 24(02), A01. https://doi.org/10.22323/2.24020201
40. Intermann, K. (2023), Science Communication and Public Trust in Science. Interdisciplinary Science Reviews, 48(2), s. 350-365.
41. Keng, T.-E., & Cheng, M.-Y. (2023), How do Researchers Use Social Media for Science Communication? Bulletin of Science, Technology & Society, 43(1-2), s. 42-52. https://doi.org/10.1177/02704676231165654
42. Kessler, S. H., Mahl, D., Schäfer, M. S. and Volk, S. C. (2025), Science Communication in the age of Artificial Intelligence. JCOM, 24(02), E. https://doi.org/10.22323/2.24020501
43. Kessler, S. H., Mahl, D., Schäfer, M. S. and Volk, S. C. (2025), All Eyez on AI: A Roadmap for Science Communication Research in the Age of Artificial Intelligence. Journal of Science Communication, 24(02), Y01. https://doi.org/10.22323/2.24020401
44. Kupper, F., Moreno-Castro, C. & Fornetti, A. (2021), Rethinking Science Communication in a Changing Landscape. Journal of Science Communication, 20(3), E. https://doi.org/10.22323/2.20030501
45. Kushnir, I. (2025), Thematic Analysis in the Area of Education: A Practical Guide. Cogent Education, 12(1), https://doi.org/10.1080/2331186X.2025.2471645
46. Leidecker-Sandmann, M., Lüders, T., Moser, C., Boger, V. R. and Lehmkuhl, M. (2025), More Than Humanoid Robots and Cyborgs? How German Print Media Visualize Articles on Artificial Intelligence. JCOM, 24(02), A09. https://doi.org/10.22323/2.24020209
47. Li, W., Xu, S., Zheng, X., & Sun, R. (2024), Bridging the Knowledge Gap in Artificial Intelligence: The Roles of Social Media Exposure and Information Elaboration. Science Communication, 46(4), s. 399-430. https://doi.org/10.1177/10755470241232352
48. Li, Y. & Guo, M. (2021), Scientific Literacy in Communicating Science and Socio-Scientific Issues: Prospects and Challenges. Frontiers in Psychology, 12, s. 1-15.
49. Liao, W., Weisman, W., & Thakur, A. (2024), On the Motivations to Seek Information From Artificial Intelligence Agents Versus Humans: A Risk Information Seeking and Processing Perspective. Science Communication, 46(4), s. 458-486. https://doi.org/10.1177/10755470241232993
50. Lyons, S. & Lidberg, J. (2024), When the Public Does not Trust Science: What can Journalists Do About It? Australian Journalism Review, 46(2), s. 249-269
51. Metag, J., Wintterlin, F., Klinger, K. (2023), Editorial: Science Communication in the Digital Age—New Actors, Environments, and Practices. Media and Communication, 11(1), s. 212-216.
52. Momme, M. J., Hendriks, F., Enzingmüller, C. (2025), From Participation to Trust? Understanding Trust Dynamics in Participatory Science Communication. Science Communication, OnlineFirst. https://doi.org/10.1177/10755470251333399
53. Oh, J., Sudarshan, S., Jin, F., Nah, S. & Yu, N. (2020), How 360-Degree Video Influences Content Perceptions and Environmental Behavior: The Moderating Effect of Environmental Self-Efficacy. Science Communication, 42(4), https://doi.org/10.1177/1075547020932174
54. Ou, M., Ho, S. S., & Wijaya, S. A. (2025), Harnessing AI to Address Misinformation on Cultivated Meat: The Impact of Chatbot Expertise and Correction Sidedness. Science Communication, 0(0). https://doi.org/10.1177/10755470251315097
55. Palm, R., Kingsland, J. T., & Bolsen, T. (2025), Framing Affects Support for the Development of Artificial Intelligence in the United States. Science Communication, 0(0). https://doi.org/10.1177/10755470251317172
56. Peng, Y. (2020), The Ideological Divide in Public Perceptions of Self-Driving Cars. Public Understanding of Science, 29(4), s. 436-451. https://doi.org/10.1177/0963662520917339
57. Peng, Y. (2022), The Role of Ideological Dimensions in Shaping Acceptance of Facial Recognition Technology and Reactions to Algorithm Bias. Public Understanding of Science, 32(2), s. 190-207. https://doi.org/10.1177/09636625221113131
58. Peng, B., & Li, D. (2026), Artificial intelligence in Digital Media, Humanities, and Information Science: A Multidimensional Analysis of Research Trends and User Perceptions. Humanities and Social Sciences Communications, 13(76). https://doi.org/10.1057/s41599-025-06372-9
59. Peter, J. & Kühne, R. (2018), The New Frontier in Communication Research: Why We Should Study Social Robots. Media and Communication, 6(6), s. 73-76.
60. QUEST. (2025), Quality and Effectiveness in Science and Technology Communication https://questproject.eu/ (Erişim Tarihi: 15.10.2025).
61. Richter, V., Katzenbach, C. and Zeng, J. (2025), Negotiating AI(s) Futures: Competing Imaginaries of AI by Stakeholders in the US, China, and Germany. JCOM, 24(02), A08. https://doi.org/10.22323/2.24020208
62. Roedema, T., Broerse, J. E. W. and Kupper, J. F. H. (2021), “Who is Going to Believe Me, If I Say ‘I'm a Researcher?’” — Scientists' Role Repertoires in Online Public Engagement JCOM, 20(03), A03. https://doi.org/10.22323/2.20030203
63. Salman, H. A., Ahmad, M. A., Ibrahim, R., & Mahmood, J. (2025), Systematic Analysis of Generative AI Tools Integration in Academic Research and Peer Review. Online Journal of Communication and Media Technologies, 15(1), e202502. https://doi.org/10.30935/ojcmt/15832
64. Samuel, G., Diedericks, H., & Derrick, G. (2020), Population Health AI Researchers’ Perceptions of the Public Portrayal of AI: A Pilot Study. Public Understanding of Science, 30(2), s. 196-211. https://doi.org/10.1177/0963662520965490
65. Sci-Co+. (2025), High Professional Skills for Advanced Scientific Communication. https://www.scicoplus.org/ (Erişim Tarihi: 20.10.2025).
66. Schäfer, M. S., Kremer, B., Mede, N. G. and Fischer, L. (2024), Trust in Science, Trust in ChatGPT? How Germans Think About Generative AI as a Source in Science Communication. JCOM, 23(09), A04. https://doi.org/10.22323/2.23090204
67. Seyitoğlu, F., & Ivanov, S. (2024), Robots and Emotional Intelligence: A Thematic Analysis. Technology in Society, 77, https://doi.org/10.1016/j.techsoc.2024.102512
68. Sieber, R., Brandusescu, A., Adu-Daako, A., & Sangiambut, S. (2024), Who are the Publics Engaging in AI? Public Understanding of Science, 33(5), s. 634-653. https://doi.org/10.1177/09636625231219853
69. Silva Luna, D., Broer, I., Bilandzic, H., Taddicken, M., Schuller, B. W., & Bürger, M. (2025), Quality in Science Communication with Communicative Artificial İntelligence: A Principle-Based Framework. Public Understanding of Science, 0(0). https://doi.org/10.1177/09636625251328854
70. Taddicken, M. and Krämer, N. (2021), Public Online Engagement with Science Information: on the Road to a Theoretical Framework and a Future Research Agenda JCOM, 20(03), A05. https://doi.org/10.22323/2.20030205
71. Tandoc, E. C., Seet, S., Chan, V. X., & Wong, P. J. O. (2025), Exploring AI İdentity: The Media Framing of Communicative Artificial İntelligence in Singapore’s News Sites. Public Understanding of Science, 0(0). https://doi.org/10.1177/09636625251317970
72. Tsimpoukis, P. (2025), Contesting Dominant AI Narratives on an Industry-Shaped Ground: Public Discourse and Actors Around AI in the French Press and Social Media (2012-2022). JCOM, 24(02), A10. https://doi.org/10.22323/2.24020210
73. Trench, B., & Bucchi, M. (2010), Science Communication, an Emerging Discipline. Journal of Science Communication, 9(3), C03.
74. UYZS. (2021), Ulusal Yapay Zekâ Stratejisi 2021-2025. https://bilgem.tubitak.gov.tr/wp-content/uploads/sites/8/TR-UlusalYZStratejisi2021-2025-1.pdf (Erişim Tarihi: 12.08.2025).
75. Većkalov, B., van Stekelenburg, A., van Harreveld, F., & Rutjens, B. T. (2023), Who Is Skeptical About Scientific Innovation? Examining Worldview Predictors of Artificial Intelligence, Nanotechnology, and Human Gene Editing Attitudes. Science Communication, 45(3), s. 337-366. https://doi.org/10.1177/10755470231184203
76. Villares, R., Pérez-Llantada, C. (2025), Digital Science Communication Training: Approaching Methods, Frameworks, and Outcomes. (Eds.: M. Martínez Vázquez, D. N. Cáceres, S. C. Madinabeitia), Fragments of Meaning: Dialogues in Language, Literature, and Culture, s. 91-101, Sevilla: Enredars Publicaciones.
77. Volk, S. C., Schäfer, M. S., Lombardi, D., Mahl, D., & Yan, X. (2024), How Generative Artificial Intelligence Portrays Science: Interviewing Chatgpt From The Perspective of Different Audience Segments. Public Understanding of Science, 34(2), 132-153. https://doi.org/10.1177/09636625241268910
78. Wagner, W., Viidalepp, A., Idoiaga-Mondragon, N., Talves, K., Lillemäe, E., Pekarev, J., & Otsus, M. (2023), Lay Representations of Artificial Intelligence and Autonomous Military Machines. Public Understanding of Science, 32(7), s. 926-943. https://doi.org/10.1177/09636625231167071
79. Walter, C. E. and Friesike, S. (2025), Behind the Screens: How Algorithmic Imaginaries Shape Science Content on Social Media. JCOM, 24(02), A02. https://doi.org/10.22323/2.24020202
80. Wang, W., & Downey, J. (2025), Mapping the Sociotechnical Imaginaries of Generative AI in UK, US, Chinese and Indian Newspapers. Public Understanding of Science, 0(0). https://doi.org/10.1177/09636625251328518
81. Wang, J., & Peng, L. (2023), Striking an Emotional Chord: Effects of Emotional Appeals and Chatbot Anthropomorphism on Persuasive Science Communication. Science Communication, 45(4), s. 485-511. https://doi.org/10.1177/10755470231194583
82. Weitkamp, E., Milani, E., Ridgway, A. and Wilkinson, C. (2021), Exploring the Digital Media Ecology: Insights From a Study of Healthy Diets and Climate Change Communication on Digital and Social Media. JCOM, 20(03), A02. https://doi.org/10.22323/2.20030202
83. Wen, C.-H. R. and Chen, Y.-N. K. (2024), Understanding Public Perceptions of Revolutionary Technology: The Role of Political Ideology, Knowledge, and News Consumption. JCOM, 23(05), A07. https://doi.org/10.22323/2.23050207
84. Westerman, D., Edwards, A. P., Edwards, C., Luo, Z., & Spence, P. R. (2020), I-It, I-Thou, I-robot: The Perceived Humanness of AI in Human-Machine Communication. Communication Studies, 71(3), s. 393–408. https://doi.org/10.1080/10510974.2020.1749683
85. Xu, X., Lin, A., C. & Chen, H. (2023), Exploring COVID-19 Vaccine Misinformation Exposure, Beliefs, Fear, and Information Avoidance via the Stimulus–Organism–Response Framework. Science Communication, 45(6), https://doi.org/10.1177/10755470231207
86. Yang, J. Z., Arpan, L., Ophir, Y., & Shah, P. (2025), Value-Based Narratives Foster Trust in Scientists and Communication Behaviors. Science Communication, 0(0). https://doi.org/10.1177/10755470251345234
87. Zhu, Y., & Chu, J. (2025), Should We Express Gratitude in Human–AI İnteraction: The Online Public’s Moral Stance Toward Artificial Intelligence Assistants in China. Public Understanding of Science, 0(0). https://doi.org/10.1177/09636625251314337