Research Article
BibTex RIS Cite

THE PRESENCE OF AI-GENERATED FAKE NEWS ON SOCIAL MEDIA:THE CASE OF TEYİT.ORG

Year 2025, Volume: 34 Issue: Uygarlığın Dönüşümü - Sosyal Bilimlerin Bakışıyla Yapay Zekâ, 255 - 274, 20.07.2025

Abstract

The advent of artificial intelligence (AI) technologies, which represent a pivotal nexus in contemporary technological evolution, has engendered a newfound capacity to generate highly realisticimages and videos. This capacity, however, is not without its potential implications, particularly with regard to the dissemination of misinformation through the medium of AI-generated content. The employment of artificial intelligence technologies in the production and detection of fake news has emerged as a novel research domain that is garnering increasing attention in academic circles. A review of the extant literature indicates that research on artificial intelligence and fake news has focused predominantly on technologies for detecting such information. Research on the channels through which fake news is disseminated and the characteristics of such content is extremely limited. The present study focuses on the role of artificial intelligence technologies in the production of fake news and its reflection on social media platforms. From this perspective, the objective of the present study is to examine the prevalence of disinformation generated by artificial intelligence, with a focus on its potential to deceive, the subjects it addresses, the social media platforms on which it disseminates, and the types of information it contains. In accordance with the predetermined objective, a keyword search was conducted on the verification platform teyit.org between January 1, 2025 and March 31, 2025 using the keyword “artificial intelligence.” A content analysis of 24 fake news articles produced by artificial intelligence was conducted as a result of the aforementioned search. The findings of the study substantiate the utilization of artificial intelligence technologies in the fabrication of disinformation. The study’s findings indicated that such fake news predominantly appears on Instagram and TikTok, is mostly disseminated in video format, and primarily focuses on topics related to life, nature, and the environment.

References

  • Akhtar, P., Ghouri, A. M., Khan, H. U. R., Haq, M. A., Awan, U., Zahoor, N., Khan, Z. & Ashraf, A. (2023). Detecting fake news and disinformation using artificial intelligence and machine learning to avoid supply chain disruptions. Annals of Operations Research. 327(2), 633-657. https://doi.org/10.1007/s10479-022-05015-5
  • Allcott, H., & Gentzkow, M. (2017). Social media and fake news in the 2016 election. The Journal of Economic Perspectives. 31(2), 211–235. https://doi.org/10.1257/jep.31.2.211
  • Almasi, M. & Schiønning, A. (2023). Fine-tuning gpt-3 for synthetic Danish news generation. In Proceedings of the 16th International Natural Language Generation Conference, 54–68, Prague, Czechia.
  • Aydın, A. F. (2020). Post-truth dönemde sosyal medyada dezenformasyon: Covid-19 (yeni koronavirüs) pandemi süreci. Asya Studies, 4(12), 76-90. https://doi.org/10.31455/asya.740420
  • Beckett, C. (2021). New powers, new responsibilities a global survey of journalism and artificial intelligence. The London School of Economics.
  • Biswas, S. (2023). Prospective role of chat gpt in the military: According to chatgpt. Qeios. https://doi.org/doi:10.32388/8WYYOD.
  • Chadha, A., Kumar, V., Kashyap, S. & Gupta, M. (2021). Deepfake: An overview. P. K. Singh, S. T. Wierzchoń, S. Tanwar, M. Ganzha & J. J. P. C. Rodrigues (Eds.), Proceedings of second international conference on computing, communications, and cyber-security (s. 557-566). Springer.
  • Cresci, S. (2020). A decade of social bot detection. Communications of the ACM. 63. 72-83. https://doi.org/10.1145/3409116.
  • Çömlekçi, M. F. (2019). Sosyal medyada dezenformasyon ve haber doğrulama platformlarının pratikleri. Gümüşhane Üniversitesi İletişim Fakültesi Elektronik Dergisi, 7(3), 1549-1563. https://doi.org/10.19145/e-gifder.583825
  • Devarajan, G.G., Nagarajan, S.M., Amanullah, S.I., Mary, S.A., & Bashir, A.K. (2024). AI-assisted deep NLP-based approach for prediction of fake news from social media users. IEEE Transactions on Computational Social Systems, 11(4), 4975-4985,
  • Dobber, T., Metoui, N., Trilling, D., Helberger, N., & de Vreese, C. (2021). Do (microtargeted) deepfakes have real effects on political attitudes? International Journal of Press/Politics, 26(1), 69-91. https://doi.org/10.1177/1940161220944364
  • El Gody, A. (2021). Using artificial intelligence in the Al Jazeera newsroom to control fake news. Al Jazeera Media Institute.
  • Erkan, G. & Ayhan, A. (2018). Siyasal iletişimde dezenformasyon ve sosyal medya: Bir doğrulama platformu olarak teyit.org. Akdeniz Üniversitesi İletişim Fakültesi Dergisi (29. Özel Sayısı), 202-223. https://doi.org/10.31123/akil.458933
  • Fallis D. (2021). The epistemic threat of deepfakes. Philosophy & Technology, 34(4), 623–643. https://doi.org/10.1007/s13347-020-00419-2
  • Ferrara, E. (2023). Social bot detection in the age of ChatGPT: Challenges and opportunities. First Monday, 28(6). https://doi.org/10.5210/fm.v28i6.13185
  • Ferrara, E., Varol, O., Davis, C. B., Menczer, F. & Flammini, A. (2016). The rise of social bots. Communications of the ACM 59(7), 96-104.
  • Floridi, L., & Chiriatti, M. (2020). GPT-3: Its nature, scope, limits, and consequences. Minds and Machines: Journal for Artificial Intelligence, Philosophy and Cognitive Science, 30(4), 681–694. https://doi.org/10.1007/s11023-020-09548-1
  • Fusco, F. (2022). Artificial intelligence and fake news: Criminal aspects in Pakistan and Saudi Arabia. Pakistan Journal of Criminology. 14 (4), 19-33.
  • Gelfert, A. (2018). Fake news: A definition. Informal Logic. 38 (1), 84-117. https://doi.org/10.22329/il.v38i1.5068
  • Godulla, A., Hoffmann, C. P., & Seibert, D. (2021). Dealing with deepfakes – an interdisciplinary examination of the state of research and implications for communication studies. SCM Studies in Communication and Media. 10(1), 72-96. https://doi.org/10.5771/2192-4007-2021-1-72
  • Graves, L. (2016). Deciding what's true: the rise of political fact-checking in American journalism. Columbia University Press.
  • Guess, A. M. & Lyons, B. A. (2020). Misinformation, disinformation, and online propaganda. N. Persily and J. A. Tucker (Eds.), Social Media and Democracy - The State of the Field, Prospects for Reform (s. 10-33). Cambridge University Press.
  • Helm, J. M., Swiergosz, A. M., Haeberle, H. S., Karnuta, J. M., Schaffer, J. L., Krebs, V. E., Spitzer, A. I., & Ramkumar, P. N. (2020). Machine learning and artificial ıntelligence: Definitions, applications, and future directions. Current reviews in musculoskeletal medicine, 13(1), 69–76. https://doi.org/10.1007/s12178-020-09600-8
  • Joshi, V. & Patel, S. (2024). Unveiling deception: a gan-based unsupervised learning approach for real-time generation and detection of text-based fake news. Journal of Electrical Systems. 20, 6189-6195. https://doi.org/10.52783/jes.6586.
  • Kaplan, A., & Haenlein, M. (2019). Siri, siri, in my hand: Who’s the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence. Business Horizons, 62, 15-25. https://doi.org/10.1016/j.bushor.2018.08.004
  • Khodabakhsh, A., Ramachandra, R. & Busch, C. (2019). Subjective evaluation of media consumer vulnerability to fake audiovisual content. 2019 Eleventh International Conference on Quality of Multimedia Experience (QoMEX), Berlin, Germany, 1-6, https://doi.org/doi: 10.1109/QoMEX.2019.8743316.
  • Kietzmann, J., Lee, L. W., McCarthy, I. P., McCarthy, I. P., & Kietzmann, T. C. (2020). Deepfakes: Trick or treat? Business Horizons, 63(2), 135–146. https://doi.org/10.1016/J.BUSHOR.2019.11.006
  • Kirchengast, T. (2020) Deepfakes and image manipulation: Criminalisation and control. Information & Communications Technology Law, 29(3), 308-323. https://doi.org/10.1080/13600834.2020.1794615
  • Kleinheksel, A. J., Rockich-Winston, N., Tawfik, H. & Wyatt, T. R. (2020). Demystifying content analysis. American Journal of Pharmaceutical Education. 84(1). https://doi.org/doi: 10.5688/ajpe7113.
  • Krippendorff, K. (2018). Content analysis - an introduction to its methodology (4th ed.). Sage Publications.
  • Lazer, D. M. J., Baum, M. A., Benkler, Y., Berinsky, A. J., Greenhill, K. M., Menczer, F and Zittrain, J. L. (2018). The science of fake news. Science, 359(6380), 1094-1096. https://doi.org/10.1126/science.aao2998
  • Levy, N. (2017). The bad news about fake news. Social Epistemology Review and Reply Collective 6, (8), 20-36.
  • Maras, M. & Alexandrou, A. (2018) Determining authenticity of video evidence in the age of artificial intelligence and in the wake of deepfake videos. The International Journal of Evidence & Proof, 23, 255-262. https://doi.org/10.1177/1365712718807226
  • Minsky, M. L. (1968). Semantic information processing. The MIT Press.
  • Narang, P. & Sharma, U. (2021). A study on artificial intelligence techniques for fake news detection. 2021 International Conference on Technological Advancements and Innovations (ICTAI), Tashkent, Uzbekistan, 482-487. doi: 10.1109/ICTAI53825.2021.9673252.
  • Nazar, S. & Bustam, R. (2020). Artificial intelligence and new level of fake news. IOP Conference Series: Materials Science and Engineering. 879. Bandung, Indonesia. https://doi.org/10.1088/1757-899X/879/1/012006.
  • Neuendorf, K. & Kumar, A. (2016). Content analysis. G. Mazzoleni (Eds.), The International Encyclopedia of Political Communication (s. 1-10). Wiley-Blackwell. https://doi.org/10.1002/9781118541555.wbiepc065.
  • Nyilasy, G. (2019) Fake news: When the dark side of persuasion takes over. International Journal of Advertising, 38(2), 336-342, https://doi.org/10.1080/02650487.2019.1586210
  • Özsalih, A. (2023). Yapay zekâ yoluyla oluşturulan sahte haberlerin medya gündemini belirlemesi. The Turkish Online Journal of Design, Art and Communication, 13(3), 533-550. https://doi.org/10.7456/tojdac.1285554
  • Pantserev, K. A. (2020). The malicious use of ai-based deepfake technology as the new threat to psychological security and political stability, H. Jahankhani, S. ¬Kendzierskyj, N. ¬Chelvachandran & J. ¬Ibarra (Eds.), -Cyber defence in the¬age of ¬ai, smart societies and augmented humanity (s. 37-56). Springer.
  • Paredes, D. G. (2023). Strategies based on artificial intelligence for the detection of fake news. AWARI; 4, 1-6. https://doi.org/10.47909/awari.58
  • Paschen, J. (2020), Investigating the emotional appeal of fake news using artificial intelligence and human contributions. Journal of Product & Brand Management, (29)2, 223-233. https://doi.org/10.1108/JPBM-12-2018-2179
  • Potthast, M., Kiesel, J., Reinartz, K., Bevendorff, J., & Stein, B. (2017). A stylometric inquiry into hyperpartisan and fake news. arXiv: Computation and Language. https://arxiv.org/abs/1702.05638
  • Raza, S., Paulen-Patterson, D. & Ding, C. (2025). Fake news detection: Comparative evaluation of BERT-like models and large language models with generative AI-annotated data. Knowl Inf Syst. 67, 3267–3292. https://doi.org/10.1007/s10115-024-02321-1
  • Rini, R. (2017). Fake news and partisan epistemology. Kennedy Institute of Ethics Journal. 27(S2), 43-64. https://doi.org/10.1353/ken.2017.0025
  • Roumeliotis, K.I., Tselikas, N.D., Nasiopoulos, D.K. (2025). Fake news detection and classification: A comparative study of convolutional neural networks, large language models, and natural language processing models. Future Internet. 17, 28. https://doi.org/10.3390/fi17010028
  • Shu, K., Sliva, A.L., Wang, S., Tang, J., & Liu, H. (2017). Fake news detection on social media: A data mining perspective. ArXiv, https://doi.org/10.48550/arXiv.1708.01967
  • Swaroop, T.S. (2024). Social media and the influence of fake news detection based on artificial intelligence. ShodhKosh: Journal of Visual and Performing Arts, 5(7), 77–87. https://doi.org/ 10.29121/shodhkosh.v5.i7.2024.1955
  • Törnberg, P. (2023). Chatgpt-4 outperforms experts and crowd workers in annotating political Twitter messages with zero-shot learning. ArXiv. https://doi.org/10.48550/arxiv.2304.06588
  • Ulusoy, H. ve Kaya İlhan, Ç. (2025). Siyasal iletişimde yapay zekâ etkisi ve deepfake (derin sahte) dezenformasyonu: 2024 ABD başkanlık seçimleri örneği. TRT Akademi, 10(23), 42-73. https://doi.org/10.37679/trta.1563828
  • Vincent, V. U. (2021). Integrating intuition and artificial intelligence in organizational decision-making. Business Horizons. (64)3, 425-438. https://doi.org/10.1016/j.bushor.2021.02.008
  • Vosoughi, S., Roy, D., & Aral, S. (2018). The spread of true and false news online. Science (New York, N.Y.), 359(6380), 1146–1151. https://doi.org/10.1126/science.aap9559
  • Wardle, C. & Derakhshan, H. (2017). Information disorder: toward an interdisciplinary framework for research and policy making. Council of Europe. https://rm.coe.int/information-disorder-report-november-2017/1680764666

YAPAY ZEKÂ İLE SAHTE HABER ÜRETİMİNİN SOSYAL MEDYADAKİ GÖRÜNÜMÜ: TEYİT.ORG ÖRNEĞİ

Year 2025, Volume: 34 Issue: Uygarlığın Dönüşümü - Sosyal Bilimlerin Bakışıyla Yapay Zekâ, 255 - 274, 20.07.2025

Abstract

Modern teknolojik gelişmenin yeni halkası olan yapay zekâ teknolojileri, gerçekçi görüntüler ve videolar üretebilme yetenekleri nedeniyle sahte haber üretiminde kullanılabilmektedir. Sahte haberlerin üretimi ve tespitinde yapay zekâ teknolojilerinin kullanımı, akademik çevrelerde giderek daha sık incelenen yeni bir araştırma alanı olarak öne çıkmaktadır. Mevcut literatür, yapay zekâ ve sahte haberlerle ilgili çalışmaların ağırlıklı olarak bu tür bilgileri tespit etmeye yönelik teknolojilerle ilgilendiğini ortaya koymaktadır. Sahte haberlerin yayıldığı kanallar ve bu tür içeriklerin özellikleriyle ilgili araştırmalar son derece sınırlıdır. Bu çalışma, sahte haber üretiminde yapay zekâ teknolojilerinin rolüne ve sosyal medyadaki görünümüne odaklanmaktadır. Buradan hareketle çalışmanın amacı, yapay zekâ tarafından üretilen sahte haberlerin varlığını, yanıltma potansiyeli, hitap ettiği konular, yayıldığı sosyal medya platformları ve içerdiği bilgi türleri açısından analiz etmektir. Belirlenen amaç doğrultusunda, 1 Ocak 2025-31 Mart 2025 tarihleri arasında teyit.org doğrulama platformunda yapay zekâ anahtar kelimesi ile arama yapılmış ve arama sonucu elde edilen yapay zekâ ile üretilmiş 24 sahte haberin içerik analizi yapılmıştır. Araştırmanın sonuçları, yapay zekâ teknolojilerinin sahte haber üretme amacıyla kullanıldığını desteklemektedir. Araştırmada en çok Instagram ve TikTok'ta görülen ve daha çok video içerikler şeklinde yayılan sahte haber içeriklerinde, yaşam, doğa ve çevreyle ilgili konuların öncelikli olduğu tespit edilmiştir.

References

  • Akhtar, P., Ghouri, A. M., Khan, H. U. R., Haq, M. A., Awan, U., Zahoor, N., Khan, Z. & Ashraf, A. (2023). Detecting fake news and disinformation using artificial intelligence and machine learning to avoid supply chain disruptions. Annals of Operations Research. 327(2), 633-657. https://doi.org/10.1007/s10479-022-05015-5
  • Allcott, H., & Gentzkow, M. (2017). Social media and fake news in the 2016 election. The Journal of Economic Perspectives. 31(2), 211–235. https://doi.org/10.1257/jep.31.2.211
  • Almasi, M. & Schiønning, A. (2023). Fine-tuning gpt-3 for synthetic Danish news generation. In Proceedings of the 16th International Natural Language Generation Conference, 54–68, Prague, Czechia.
  • Aydın, A. F. (2020). Post-truth dönemde sosyal medyada dezenformasyon: Covid-19 (yeni koronavirüs) pandemi süreci. Asya Studies, 4(12), 76-90. https://doi.org/10.31455/asya.740420
  • Beckett, C. (2021). New powers, new responsibilities a global survey of journalism and artificial intelligence. The London School of Economics.
  • Biswas, S. (2023). Prospective role of chat gpt in the military: According to chatgpt. Qeios. https://doi.org/doi:10.32388/8WYYOD.
  • Chadha, A., Kumar, V., Kashyap, S. & Gupta, M. (2021). Deepfake: An overview. P. K. Singh, S. T. Wierzchoń, S. Tanwar, M. Ganzha & J. J. P. C. Rodrigues (Eds.), Proceedings of second international conference on computing, communications, and cyber-security (s. 557-566). Springer.
  • Cresci, S. (2020). A decade of social bot detection. Communications of the ACM. 63. 72-83. https://doi.org/10.1145/3409116.
  • Çömlekçi, M. F. (2019). Sosyal medyada dezenformasyon ve haber doğrulama platformlarının pratikleri. Gümüşhane Üniversitesi İletişim Fakültesi Elektronik Dergisi, 7(3), 1549-1563. https://doi.org/10.19145/e-gifder.583825
  • Devarajan, G.G., Nagarajan, S.M., Amanullah, S.I., Mary, S.A., & Bashir, A.K. (2024). AI-assisted deep NLP-based approach for prediction of fake news from social media users. IEEE Transactions on Computational Social Systems, 11(4), 4975-4985,
  • Dobber, T., Metoui, N., Trilling, D., Helberger, N., & de Vreese, C. (2021). Do (microtargeted) deepfakes have real effects on political attitudes? International Journal of Press/Politics, 26(1), 69-91. https://doi.org/10.1177/1940161220944364
  • El Gody, A. (2021). Using artificial intelligence in the Al Jazeera newsroom to control fake news. Al Jazeera Media Institute.
  • Erkan, G. & Ayhan, A. (2018). Siyasal iletişimde dezenformasyon ve sosyal medya: Bir doğrulama platformu olarak teyit.org. Akdeniz Üniversitesi İletişim Fakültesi Dergisi (29. Özel Sayısı), 202-223. https://doi.org/10.31123/akil.458933
  • Fallis D. (2021). The epistemic threat of deepfakes. Philosophy & Technology, 34(4), 623–643. https://doi.org/10.1007/s13347-020-00419-2
  • Ferrara, E. (2023). Social bot detection in the age of ChatGPT: Challenges and opportunities. First Monday, 28(6). https://doi.org/10.5210/fm.v28i6.13185
  • Ferrara, E., Varol, O., Davis, C. B., Menczer, F. & Flammini, A. (2016). The rise of social bots. Communications of the ACM 59(7), 96-104.
  • Floridi, L., & Chiriatti, M. (2020). GPT-3: Its nature, scope, limits, and consequences. Minds and Machines: Journal for Artificial Intelligence, Philosophy and Cognitive Science, 30(4), 681–694. https://doi.org/10.1007/s11023-020-09548-1
  • Fusco, F. (2022). Artificial intelligence and fake news: Criminal aspects in Pakistan and Saudi Arabia. Pakistan Journal of Criminology. 14 (4), 19-33.
  • Gelfert, A. (2018). Fake news: A definition. Informal Logic. 38 (1), 84-117. https://doi.org/10.22329/il.v38i1.5068
  • Godulla, A., Hoffmann, C. P., & Seibert, D. (2021). Dealing with deepfakes – an interdisciplinary examination of the state of research and implications for communication studies. SCM Studies in Communication and Media. 10(1), 72-96. https://doi.org/10.5771/2192-4007-2021-1-72
  • Graves, L. (2016). Deciding what's true: the rise of political fact-checking in American journalism. Columbia University Press.
  • Guess, A. M. & Lyons, B. A. (2020). Misinformation, disinformation, and online propaganda. N. Persily and J. A. Tucker (Eds.), Social Media and Democracy - The State of the Field, Prospects for Reform (s. 10-33). Cambridge University Press.
  • Helm, J. M., Swiergosz, A. M., Haeberle, H. S., Karnuta, J. M., Schaffer, J. L., Krebs, V. E., Spitzer, A. I., & Ramkumar, P. N. (2020). Machine learning and artificial ıntelligence: Definitions, applications, and future directions. Current reviews in musculoskeletal medicine, 13(1), 69–76. https://doi.org/10.1007/s12178-020-09600-8
  • Joshi, V. & Patel, S. (2024). Unveiling deception: a gan-based unsupervised learning approach for real-time generation and detection of text-based fake news. Journal of Electrical Systems. 20, 6189-6195. https://doi.org/10.52783/jes.6586.
  • Kaplan, A., & Haenlein, M. (2019). Siri, siri, in my hand: Who’s the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence. Business Horizons, 62, 15-25. https://doi.org/10.1016/j.bushor.2018.08.004
  • Khodabakhsh, A., Ramachandra, R. & Busch, C. (2019). Subjective evaluation of media consumer vulnerability to fake audiovisual content. 2019 Eleventh International Conference on Quality of Multimedia Experience (QoMEX), Berlin, Germany, 1-6, https://doi.org/doi: 10.1109/QoMEX.2019.8743316.
  • Kietzmann, J., Lee, L. W., McCarthy, I. P., McCarthy, I. P., & Kietzmann, T. C. (2020). Deepfakes: Trick or treat? Business Horizons, 63(2), 135–146. https://doi.org/10.1016/J.BUSHOR.2019.11.006
  • Kirchengast, T. (2020) Deepfakes and image manipulation: Criminalisation and control. Information & Communications Technology Law, 29(3), 308-323. https://doi.org/10.1080/13600834.2020.1794615
  • Kleinheksel, A. J., Rockich-Winston, N., Tawfik, H. & Wyatt, T. R. (2020). Demystifying content analysis. American Journal of Pharmaceutical Education. 84(1). https://doi.org/doi: 10.5688/ajpe7113.
  • Krippendorff, K. (2018). Content analysis - an introduction to its methodology (4th ed.). Sage Publications.
  • Lazer, D. M. J., Baum, M. A., Benkler, Y., Berinsky, A. J., Greenhill, K. M., Menczer, F and Zittrain, J. L. (2018). The science of fake news. Science, 359(6380), 1094-1096. https://doi.org/10.1126/science.aao2998
  • Levy, N. (2017). The bad news about fake news. Social Epistemology Review and Reply Collective 6, (8), 20-36.
  • Maras, M. & Alexandrou, A. (2018) Determining authenticity of video evidence in the age of artificial intelligence and in the wake of deepfake videos. The International Journal of Evidence & Proof, 23, 255-262. https://doi.org/10.1177/1365712718807226
  • Minsky, M. L. (1968). Semantic information processing. The MIT Press.
  • Narang, P. & Sharma, U. (2021). A study on artificial intelligence techniques for fake news detection. 2021 International Conference on Technological Advancements and Innovations (ICTAI), Tashkent, Uzbekistan, 482-487. doi: 10.1109/ICTAI53825.2021.9673252.
  • Nazar, S. & Bustam, R. (2020). Artificial intelligence and new level of fake news. IOP Conference Series: Materials Science and Engineering. 879. Bandung, Indonesia. https://doi.org/10.1088/1757-899X/879/1/012006.
  • Neuendorf, K. & Kumar, A. (2016). Content analysis. G. Mazzoleni (Eds.), The International Encyclopedia of Political Communication (s. 1-10). Wiley-Blackwell. https://doi.org/10.1002/9781118541555.wbiepc065.
  • Nyilasy, G. (2019) Fake news: When the dark side of persuasion takes over. International Journal of Advertising, 38(2), 336-342, https://doi.org/10.1080/02650487.2019.1586210
  • Özsalih, A. (2023). Yapay zekâ yoluyla oluşturulan sahte haberlerin medya gündemini belirlemesi. The Turkish Online Journal of Design, Art and Communication, 13(3), 533-550. https://doi.org/10.7456/tojdac.1285554
  • Pantserev, K. A. (2020). The malicious use of ai-based deepfake technology as the new threat to psychological security and political stability, H. Jahankhani, S. ¬Kendzierskyj, N. ¬Chelvachandran & J. ¬Ibarra (Eds.), -Cyber defence in the¬age of ¬ai, smart societies and augmented humanity (s. 37-56). Springer.
  • Paredes, D. G. (2023). Strategies based on artificial intelligence for the detection of fake news. AWARI; 4, 1-6. https://doi.org/10.47909/awari.58
  • Paschen, J. (2020), Investigating the emotional appeal of fake news using artificial intelligence and human contributions. Journal of Product & Brand Management, (29)2, 223-233. https://doi.org/10.1108/JPBM-12-2018-2179
  • Potthast, M., Kiesel, J., Reinartz, K., Bevendorff, J., & Stein, B. (2017). A stylometric inquiry into hyperpartisan and fake news. arXiv: Computation and Language. https://arxiv.org/abs/1702.05638
  • Raza, S., Paulen-Patterson, D. & Ding, C. (2025). Fake news detection: Comparative evaluation of BERT-like models and large language models with generative AI-annotated data. Knowl Inf Syst. 67, 3267–3292. https://doi.org/10.1007/s10115-024-02321-1
  • Rini, R. (2017). Fake news and partisan epistemology. Kennedy Institute of Ethics Journal. 27(S2), 43-64. https://doi.org/10.1353/ken.2017.0025
  • Roumeliotis, K.I., Tselikas, N.D., Nasiopoulos, D.K. (2025). Fake news detection and classification: A comparative study of convolutional neural networks, large language models, and natural language processing models. Future Internet. 17, 28. https://doi.org/10.3390/fi17010028
  • Shu, K., Sliva, A.L., Wang, S., Tang, J., & Liu, H. (2017). Fake news detection on social media: A data mining perspective. ArXiv, https://doi.org/10.48550/arXiv.1708.01967
  • Swaroop, T.S. (2024). Social media and the influence of fake news detection based on artificial intelligence. ShodhKosh: Journal of Visual and Performing Arts, 5(7), 77–87. https://doi.org/ 10.29121/shodhkosh.v5.i7.2024.1955
  • Törnberg, P. (2023). Chatgpt-4 outperforms experts and crowd workers in annotating political Twitter messages with zero-shot learning. ArXiv. https://doi.org/10.48550/arxiv.2304.06588
  • Ulusoy, H. ve Kaya İlhan, Ç. (2025). Siyasal iletişimde yapay zekâ etkisi ve deepfake (derin sahte) dezenformasyonu: 2024 ABD başkanlık seçimleri örneği. TRT Akademi, 10(23), 42-73. https://doi.org/10.37679/trta.1563828
  • Vincent, V. U. (2021). Integrating intuition and artificial intelligence in organizational decision-making. Business Horizons. (64)3, 425-438. https://doi.org/10.1016/j.bushor.2021.02.008
  • Vosoughi, S., Roy, D., & Aral, S. (2018). The spread of true and false news online. Science (New York, N.Y.), 359(6380), 1146–1151. https://doi.org/10.1126/science.aap9559
  • Wardle, C. & Derakhshan, H. (2017). Information disorder: toward an interdisciplinary framework for research and policy making. Council of Europe. https://rm.coe.int/information-disorder-report-november-2017/1680764666
There are 53 citations in total.

Details

Primary Language Turkish
Subjects Communication and Media Studies (Other)
Journal Section Articles
Authors

İbrahim Yıldız 0000-0002-2542-389X

Publication Date July 20, 2025
Submission Date May 9, 2025
Acceptance Date July 8, 2025
Published in Issue Year 2025 Volume: 34 Issue: Uygarlığın Dönüşümü - Sosyal Bilimlerin Bakışıyla Yapay Zekâ

Cite

APA Yıldız, İ. (2025). YAPAY ZEKÂ İLE SAHTE HABER ÜRETİMİNİN SOSYAL MEDYADAKİ GÖRÜNÜMÜ: TEYİT.ORG ÖRNEĞİ. Çukurova Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 34(Uygarlığın Dönüşümü - Sosyal Bilimlerin Bakışıyla Yapay Zekâ), 255-274. https://doi.org/10.35379/cusosbil.1696022