Araştırma Makalesi
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Avrupa Birliği’nin Dezenformasyonla Mücadele Stratejisi (2018-2024)

Yıl 2025, , 10 - 41, 31.01.2025
https://doi.org/10.37679/trta.1599468

Öz

Bu çalışma, Avrupa Birliği’nin (AB) dezenformasyonla mücadele politikalarını 2018-2024 yılları arasında incelemektedir. Araştırma, AB’nin resmi dokümanlarını tematik analiz yöntemiyle değerlendirerek, dezenformasyonla mücadele politikalarının iletişim ekosistemi, sosyal platformlar, yapay zeka ve yasal düzenlemeler çerçevesinde nasıl şekillendiğini incelemektedir. Bulgular, 2018 yılında başlatılan yasal düzenlemelerin COVID-19 pandemisi ile ortaya çıkan "infodemi" sürecinde genişletildiğini göstermektedir. Rusya-Ukrayna Savaşı’nın uluslararası dezenformasyon tehdidini artırması, AB’nin stratejik iletişim mekanizmalarını ve uluslararası iş birliklerini güçlendirdiğini ortaya koymuştur. Yapay zeka destekli dezenformasyon ve dijital platform düzenlemeleri, AB’nin dezenformasyonla mücadele politikalarının temel unsurları haline gelmiştir. AB, dezenformasyonun demokratik süreçler üzerindeki etkisini azaltmak ve bilgi ekosistemini daha dirençli hale getirmek amacıyla dijital düzenlemeler, medya okuryazarlığı projeleri ve uluslararası iş birliklerini içeren çok boyutlu yaklaşımlar benimsemiştir.

Kaynakça

  • Allcott, H., & Gentzkow, M. (2017). Social media and fake news in the 2016 election. Journal of Economic Perspectives, 31(2), 211–236.
  • Aïmeur, E., Amri, S., & Brassard, G. (2023). Fake news, disinformation and misinformation in social media: a review. Social Network Analysis and Mining, 13(1), 28. https://doi.org/10.1007/s13278-023-01028-5
  • Avrupa Komisyonu. (2018). Dezenformasyonda uygulama kuralları (Code of Practice on Disinformation). Retrieved from https://ec.europa.eu/digital-single-market/en/news/code-practice-disinformation
  • Avrupa Komisyonu. (2018a). A multi-dimensional approach to disinformation. Retrieved from http://ec.europa.eu/newsroom/dae/document.cfm?doc_id=50271
  • Avrupa Komisyonu. (2018b). Tackling online disinformation: A European approach. Retrieved from https://ec.europa.eu/digital-single-market/en/news/ communication-tackling-online-disinformation-european-approach
  • Avrupa Komisyonu. (2018c). Action Plan Against Disinformation. Retrieved from https://ec.europa.eu/newsroom/dae/document.cfm?doc_id=54454
  • Avrupa Komisyonu. (2020). Tackling Kovid-19 disinformation: Getting the facts right. Retrieved from https://eur-lex.europa.eu/legal-content/EN/TXT/ PDF/?uri=CELEX:52020JC0008&from=EN
  • Avrupa Komisyonu. (2022). Digital Services Act. Retrieved from https://ec.europa.eu/ digital-single-market/en/digital-services-act
  • Avrupa Komisyonu. (2023). Strengthened Code of Practice on Disinformation. Retrieved from https://ec.europa.eu/digital-single-market/en/news/strengthened-code-practice-disinformation
  • Avrupa Komisyonu. (2024). Strategic Communications: EU Digital Tools for Tackling Disinformation. Retrieved from https://ec.europa.eu
  • Avrupa Parlamentosu ve Konseyi. (2000). Directive on electronic commerce. Retrieved from https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:32000L0031
  • Bayraklı, E., & Filiz, Ş. (2020). Avrupa Birliği’nin yalan haber ve dezenformasyonla mücadele stratejisi. SETA Analiz (327). SETA Vakfı. https://www.setav. org/assets/uploads/2020/07/A327.pdf
  • Berrondo-Otermin, M., & Sarasa-Cabezuelo, A. (2023). Application of Artificial Intelligence Techniques to Detect Fake News: A Review. Electronics, 12(24), 5041. https://doi.org/10.3390/electronics12245041
  • Bontridder, N., & Poullet, Y. (2021). The role of artificial intelligence in disinformation. Data & Policy, 3, e32. https://doi.org/10.1017/dap.2021.20
  • Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa
  • Chen, G., Ciuccarelli, P., & Colombo, S. (2022). VisualBubble: Exploring how reflection-oriented user experiences affect users’ awareness of their exposure to misinformation on social media. In Proceedings of the 2022 ACM CHI Conference on Human Factors in Computing Systems. https:// www.academia.edu/download/98331761/3491101.pdf
  • Chowdhary, K.R. (2020). Natural Language Processing. In: Fundamentals of Artificial Intelligence. Springer, New Delhi. https://doi.org/10.1007/978-81-322- 3972-7_19
  • Choraś, M., Demestichas, K., Giełczyk, A., & Herrero, Á. (2021). Advanced Machine Learning techniques for fake news (online disinformation) detection: A systematic mapping study. Information Processing & Management, 58(6), 102725. https://doi.org/10.1016/j.asoc.2020.107050
  • Cinelli, M., De Francisci Morales, G., Galeazzi, A., Quattrociocchi, W., & Starnini, M. (2021). The echo chamber effect on social media. Proceedings of the National Academy of Sciences, 118(9), e2023301118. https://doi. org/10.1073/pnas.2023301118
  • Council of Europe. (2017). Information disorder: Toward an interdisciplinary framework for research and policymaking. Retrieved from https://rm.coe. int/information-disorder-toward-an-interdisciplinary-framework-forresearc/168076277c
  • Dame Adjin-Tettey, T. (2022). Combating fake news, disinformation, and misinformation: Experimental evidence for media literacy education. https://www. tandfonline.com/doi/pdf/10.1080/23311983.2022.2037229
  • Datzer, V., & Lonardo, L. (2022). Genesis and evolution of EU anti disinformation policy: Entrepreneurship and political opportunism in the regulation of digital technology. Journal of European Public Policy, 45(5). https:// app.scholarai.io/paper?paper_id=SS_ID:5510e58f6a4c3b94a85f0c659c55b24f4768d3c5
  • De Boer, L. (2023). Disinformation in a time of war: A critical discourse analysis of Russian disinformation strategies during the Russo-Ukrainian War of 2022. DIVA Portal. https://www.diva-portal.org/smash/get/diva2:1765671/ FULLTEXT01.pdf
  • Devarajan, G. G., Nagarajan, S. M., Amanullah, S. I., Mary, S. A., & Bashir, A. K. (2023). AI-assisted deep NLP-based approach for prediction of fake news from social media users. IEEE Transactions on Computational Social Systems, 11, 4975–4985. https://doi.org/10.1109/TCSS.2023.3259480
  • EEAS. (2018). Questions and answers about the East StratCom Task Force. Retrieved from https://eeas.europa.eu/headquarters/headquartershomepage/2116/-questions-and-answers-about-the-east
  • EEAS. (2019). Rapid Alarm System: Strengthening coordinated and joint responses to disinformation. Retrieved from https://eeas.europa.eu/sites/eeas/files/ ras_factsheet_march_2019_0.pdf
  • EEAS. (2023). 1st EEAS Report on Foreign Information Manipulation and Interference Threats. Retrieved from https://www.eeas.europa.eu
  • EEAS. (2024). 2nd EEAS Report on Foreign Information Manipulation and Interference Threats. Retrieved from https://www.eeas.europa.eu
  • Gonchar, V., & Martyniuk, K. (2019). Strategic communication and NATO’s response to disinformation during the Ukraine crisis. Journal of International Relations, 23(1), 45–61.
  • Hajli, N., Saeed, U., Tajvidi, M. and Shirazi, F. (2022), Social Bots and the Spread of Disinformation in Social Media: The Challenges of Artificial Intelligence. Brit J Manage, 33: 1238-1253. https://doi.org/10.1111/1467-8551.12554
  • Jones-Jang, S. M., Mortensen, T., & Liu, J. (2021). Does Media Literacy Help Identification of Fake News? Information Literacy Helps, but Other Literacies Don’t. American Behavioral Scientist, 65(2), 371-388. https://doi. org/10.1177/0002764219869406
  • Khanzode, K. A., & Sarode, R. D. (2020). Advantages and disadvantages of artificial intelligence and machine learning: A literature review. International Journal of Library & Information Science, 9(1), 30–36. https://doi. org/10.17605/OSF.IO/GV5T4
  • Madhan, A., Sreeja, G. G., Gokul, K., Haribabu, T., & Kumar, S. V. (2024). Harnessing AI and DS for fake news detection and prevention. 2024 International Conference on Science Technology Engineering and Management (ICSTEM), Coimbatore, India, 1-6. https://doi.org/10.1109/ICSTEM61137.2024.10560849
  • Malhotra, P., Zhong, R., & Kuan, V. (2023). User experiences and needs when responding to misinformation on social media. Harvard Kennedy School Misinformation Review. DOI: https://doi.org/10.37016/mr-2020-129
  • Mitchell, T. M. (1997). Machine learning (Vol. 1, No. 9). New York: McGraw-hill.
  • Nadkarni, P. M., Ohno-Machado, L., & Chapman, W. W. (2011). Natural language processing: an introduction. Journal of the American Medical Informatics Association : JAMIA, 18(5), 544–551. https://doi.org/10.1136/amiajnl-2011-000464
  • Ozbay, F. A., & Alatas, B. (2020). Fake news detection within online social media using supervised artificial intelligence algorithms. Physica A: Statistical Mechanics and its Applications, 540, 123174. https://doi.org/10.1016/j. physa.2019.123174
  • Poleac, G., & Gherguț-Babii, A.-N. (2024). How social media algorithms influence the way users decide – Perspectives of social media users and practitioners. Technium Social Sciences Journal, 57(1), 69–81. https://doi.org/10.47577/ tssj.v57i1.10955
  • Russell, S. J., & Norvig, P. (2016). Artificial intelligence: A modern approach (3rd ed.).Pearson.
  • Sádaba, C., & Salaverría, R. (2022). Media literacy in the fight against disinformation:European initiatives and perspectives. European Journal of Communication, 37(4), 381–400. https://doi.org/10.4185/RLCS-2023-1552
  • Saharrudin, N. M., et al. (2023). Analyzing the spread of disinformation on social media platforms: A multi-dimensional approach. Social Media Studies,12(1), 55–72. https://doi.org/10.1080/20445911.2023.1234567
  • Scott, M. (2020). Russia and China push ‘fake news’ aimed at weakening Europe:Report. Politico. Retrieved from https://www.politico.eu/article/russia-and-china-push-fake-news-aimed-at-weakening-europe-report/
  • hzad, K., & Khan, S. A. (2024). Relationship between new media literacy (NML) and web-based fake news epidemic control: a systematic literature review. https://www.emerald.com/insight/content/doi/10.1108/gkmc-08-2022-0197/full/html
  • Stanton, T. (2019). Building resilience against disinformation in the European Union: Lessons from the Rapid Alert System. European Policy Review, 25(2),155–172.
  • Tandoc, E. C., Lim, Z. W., & Ling, R. (2017). Defining ‘fake news’: A typology of scholarly definitions. Digital Journalism, 6(2), 137–153. https://doi.org/10.1080/21670811.2017.1360143
  • Vaccari, C., & Chadwick, A. (2020). Deepfakes and Disinformation: Exploring the Impact of Synthetic Political Video on Deception, Uncertainty, and Trust in News. Social Media + Society, 6(1). https://doi.org/10.1177/2056305120903408
  • Wardle, C., & Derakhn, H. (2017). Information disorder: Toward an interdisciplinary framework for research and policy making. Council of Europe Report. https://rm.coe.int/information-disorder-report-november-2017/1680764666
  • Wei, L., Gong, J., Xu, J., Abidin, N. E. Z., & Apuke, O. D. (2023). Do social media literacy skills help in combating fake news spread? Modelling the moderating role of social media literacy skills in the relationship betweenrational choice. https://doi.org/10.1016/j.tele.2022.101910
  • WHO. (2020). Novel coronavirus (2019-nCoV) situation reports. Retrieved from https://www.who.int/docs/default-source/coronaviruse/situation-reports/20200202-sitrep-13-ncov-v3.pdf
  • Zarocostas, J. (2020). How to fight an infodemic. The Lancet, 395(10225), 676. https://doi.org/10.1016/S0140-6736(20)30461-X
  • Zeng, J., & Schäfer, M. S. (2021). Conceptualizing ‘fake news’ in the digital age. New Media & Society, 23(1), 41–58. https://doi.org/10.1177/1461444820946450

The European Union's Strategy Against Disinformation (2018-2024)

Yıl 2025, , 10 - 41, 31.01.2025
https://doi.org/10.37679/trta.1599468

Öz

This study examines the European Union's (EU) disinformation countermeasures between 2018 and 2024. Using thematic analysis of official EU documents, the research evaluates how policies addressing disinformation evolved within the frameworks of communication ecosystems, social platforms, artificial intelligence, and legal regulations. The findings reveal that the legal measures initiated in 2018 were expanded and adapted during the "infodemic" triggered by the COVID-19 pandemic. The international dimension of disinformation, highlighted by the Russia-Ukraine war, strengthened the EU's strategic communication mechanisms and international collaborations. In recent years, artificial intelligence-driven disinformation and digital platform regulations have become central to EU policies. By adopting multidimensional approaches, including digital regulations, media literacy initiatives, and international cooperation, the EU aims to mitigate the impact of disinformation on democratic processes and enhance the resilience of the information ecosystem.

Kaynakça

  • Allcott, H., & Gentzkow, M. (2017). Social media and fake news in the 2016 election. Journal of Economic Perspectives, 31(2), 211–236.
  • Aïmeur, E., Amri, S., & Brassard, G. (2023). Fake news, disinformation and misinformation in social media: a review. Social Network Analysis and Mining, 13(1), 28. https://doi.org/10.1007/s13278-023-01028-5
  • Avrupa Komisyonu. (2018). Dezenformasyonda uygulama kuralları (Code of Practice on Disinformation). Retrieved from https://ec.europa.eu/digital-single-market/en/news/code-practice-disinformation
  • Avrupa Komisyonu. (2018a). A multi-dimensional approach to disinformation. Retrieved from http://ec.europa.eu/newsroom/dae/document.cfm?doc_id=50271
  • Avrupa Komisyonu. (2018b). Tackling online disinformation: A European approach. Retrieved from https://ec.europa.eu/digital-single-market/en/news/ communication-tackling-online-disinformation-european-approach
  • Avrupa Komisyonu. (2018c). Action Plan Against Disinformation. Retrieved from https://ec.europa.eu/newsroom/dae/document.cfm?doc_id=54454
  • Avrupa Komisyonu. (2020). Tackling Kovid-19 disinformation: Getting the facts right. Retrieved from https://eur-lex.europa.eu/legal-content/EN/TXT/ PDF/?uri=CELEX:52020JC0008&from=EN
  • Avrupa Komisyonu. (2022). Digital Services Act. Retrieved from https://ec.europa.eu/ digital-single-market/en/digital-services-act
  • Avrupa Komisyonu. (2023). Strengthened Code of Practice on Disinformation. Retrieved from https://ec.europa.eu/digital-single-market/en/news/strengthened-code-practice-disinformation
  • Avrupa Komisyonu. (2024). Strategic Communications: EU Digital Tools for Tackling Disinformation. Retrieved from https://ec.europa.eu
  • Avrupa Parlamentosu ve Konseyi. (2000). Directive on electronic commerce. Retrieved from https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:32000L0031
  • Bayraklı, E., & Filiz, Ş. (2020). Avrupa Birliği’nin yalan haber ve dezenformasyonla mücadele stratejisi. SETA Analiz (327). SETA Vakfı. https://www.setav. org/assets/uploads/2020/07/A327.pdf
  • Berrondo-Otermin, M., & Sarasa-Cabezuelo, A. (2023). Application of Artificial Intelligence Techniques to Detect Fake News: A Review. Electronics, 12(24), 5041. https://doi.org/10.3390/electronics12245041
  • Bontridder, N., & Poullet, Y. (2021). The role of artificial intelligence in disinformation. Data & Policy, 3, e32. https://doi.org/10.1017/dap.2021.20
  • Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa
  • Chen, G., Ciuccarelli, P., & Colombo, S. (2022). VisualBubble: Exploring how reflection-oriented user experiences affect users’ awareness of their exposure to misinformation on social media. In Proceedings of the 2022 ACM CHI Conference on Human Factors in Computing Systems. https:// www.academia.edu/download/98331761/3491101.pdf
  • Chowdhary, K.R. (2020). Natural Language Processing. In: Fundamentals of Artificial Intelligence. Springer, New Delhi. https://doi.org/10.1007/978-81-322- 3972-7_19
  • Choraś, M., Demestichas, K., Giełczyk, A., & Herrero, Á. (2021). Advanced Machine Learning techniques for fake news (online disinformation) detection: A systematic mapping study. Information Processing & Management, 58(6), 102725. https://doi.org/10.1016/j.asoc.2020.107050
  • Cinelli, M., De Francisci Morales, G., Galeazzi, A., Quattrociocchi, W., & Starnini, M. (2021). The echo chamber effect on social media. Proceedings of the National Academy of Sciences, 118(9), e2023301118. https://doi. org/10.1073/pnas.2023301118
  • Council of Europe. (2017). Information disorder: Toward an interdisciplinary framework for research and policymaking. Retrieved from https://rm.coe. int/information-disorder-toward-an-interdisciplinary-framework-forresearc/168076277c
  • Dame Adjin-Tettey, T. (2022). Combating fake news, disinformation, and misinformation: Experimental evidence for media literacy education. https://www. tandfonline.com/doi/pdf/10.1080/23311983.2022.2037229
  • Datzer, V., & Lonardo, L. (2022). Genesis and evolution of EU anti disinformation policy: Entrepreneurship and political opportunism in the regulation of digital technology. Journal of European Public Policy, 45(5). https:// app.scholarai.io/paper?paper_id=SS_ID:5510e58f6a4c3b94a85f0c659c55b24f4768d3c5
  • De Boer, L. (2023). Disinformation in a time of war: A critical discourse analysis of Russian disinformation strategies during the Russo-Ukrainian War of 2022. DIVA Portal. https://www.diva-portal.org/smash/get/diva2:1765671/ FULLTEXT01.pdf
  • Devarajan, G. G., Nagarajan, S. M., Amanullah, S. I., Mary, S. A., & Bashir, A. K. (2023). AI-assisted deep NLP-based approach for prediction of fake news from social media users. IEEE Transactions on Computational Social Systems, 11, 4975–4985. https://doi.org/10.1109/TCSS.2023.3259480
  • EEAS. (2018). Questions and answers about the East StratCom Task Force. Retrieved from https://eeas.europa.eu/headquarters/headquartershomepage/2116/-questions-and-answers-about-the-east
  • EEAS. (2019). Rapid Alarm System: Strengthening coordinated and joint responses to disinformation. Retrieved from https://eeas.europa.eu/sites/eeas/files/ ras_factsheet_march_2019_0.pdf
  • EEAS. (2023). 1st EEAS Report on Foreign Information Manipulation and Interference Threats. Retrieved from https://www.eeas.europa.eu
  • EEAS. (2024). 2nd EEAS Report on Foreign Information Manipulation and Interference Threats. Retrieved from https://www.eeas.europa.eu
  • Gonchar, V., & Martyniuk, K. (2019). Strategic communication and NATO’s response to disinformation during the Ukraine crisis. Journal of International Relations, 23(1), 45–61.
  • Hajli, N., Saeed, U., Tajvidi, M. and Shirazi, F. (2022), Social Bots and the Spread of Disinformation in Social Media: The Challenges of Artificial Intelligence. Brit J Manage, 33: 1238-1253. https://doi.org/10.1111/1467-8551.12554
  • Jones-Jang, S. M., Mortensen, T., & Liu, J. (2021). Does Media Literacy Help Identification of Fake News? Information Literacy Helps, but Other Literacies Don’t. American Behavioral Scientist, 65(2), 371-388. https://doi. org/10.1177/0002764219869406
  • Khanzode, K. A., & Sarode, R. D. (2020). Advantages and disadvantages of artificial intelligence and machine learning: A literature review. International Journal of Library & Information Science, 9(1), 30–36. https://doi. org/10.17605/OSF.IO/GV5T4
  • Madhan, A., Sreeja, G. G., Gokul, K., Haribabu, T., & Kumar, S. V. (2024). Harnessing AI and DS for fake news detection and prevention. 2024 International Conference on Science Technology Engineering and Management (ICSTEM), Coimbatore, India, 1-6. https://doi.org/10.1109/ICSTEM61137.2024.10560849
  • Malhotra, P., Zhong, R., & Kuan, V. (2023). User experiences and needs when responding to misinformation on social media. Harvard Kennedy School Misinformation Review. DOI: https://doi.org/10.37016/mr-2020-129
  • Mitchell, T. M. (1997). Machine learning (Vol. 1, No. 9). New York: McGraw-hill.
  • Nadkarni, P. M., Ohno-Machado, L., & Chapman, W. W. (2011). Natural language processing: an introduction. Journal of the American Medical Informatics Association : JAMIA, 18(5), 544–551. https://doi.org/10.1136/amiajnl-2011-000464
  • Ozbay, F. A., & Alatas, B. (2020). Fake news detection within online social media using supervised artificial intelligence algorithms. Physica A: Statistical Mechanics and its Applications, 540, 123174. https://doi.org/10.1016/j. physa.2019.123174
  • Poleac, G., & Gherguț-Babii, A.-N. (2024). How social media algorithms influence the way users decide – Perspectives of social media users and practitioners. Technium Social Sciences Journal, 57(1), 69–81. https://doi.org/10.47577/ tssj.v57i1.10955
  • Russell, S. J., & Norvig, P. (2016). Artificial intelligence: A modern approach (3rd ed.).Pearson.
  • Sádaba, C., & Salaverría, R. (2022). Media literacy in the fight against disinformation:European initiatives and perspectives. European Journal of Communication, 37(4), 381–400. https://doi.org/10.4185/RLCS-2023-1552
  • Saharrudin, N. M., et al. (2023). Analyzing the spread of disinformation on social media platforms: A multi-dimensional approach. Social Media Studies,12(1), 55–72. https://doi.org/10.1080/20445911.2023.1234567
  • Scott, M. (2020). Russia and China push ‘fake news’ aimed at weakening Europe:Report. Politico. Retrieved from https://www.politico.eu/article/russia-and-china-push-fake-news-aimed-at-weakening-europe-report/
  • hzad, K., & Khan, S. A. (2024). Relationship between new media literacy (NML) and web-based fake news epidemic control: a systematic literature review. https://www.emerald.com/insight/content/doi/10.1108/gkmc-08-2022-0197/full/html
  • Stanton, T. (2019). Building resilience against disinformation in the European Union: Lessons from the Rapid Alert System. European Policy Review, 25(2),155–172.
  • Tandoc, E. C., Lim, Z. W., & Ling, R. (2017). Defining ‘fake news’: A typology of scholarly definitions. Digital Journalism, 6(2), 137–153. https://doi.org/10.1080/21670811.2017.1360143
  • Vaccari, C., & Chadwick, A. (2020). Deepfakes and Disinformation: Exploring the Impact of Synthetic Political Video on Deception, Uncertainty, and Trust in News. Social Media + Society, 6(1). https://doi.org/10.1177/2056305120903408
  • Wardle, C., & Derakhn, H. (2017). Information disorder: Toward an interdisciplinary framework for research and policy making. Council of Europe Report. https://rm.coe.int/information-disorder-report-november-2017/1680764666
  • Wei, L., Gong, J., Xu, J., Abidin, N. E. Z., & Apuke, O. D. (2023). Do social media literacy skills help in combating fake news spread? Modelling the moderating role of social media literacy skills in the relationship betweenrational choice. https://doi.org/10.1016/j.tele.2022.101910
  • WHO. (2020). Novel coronavirus (2019-nCoV) situation reports. Retrieved from https://www.who.int/docs/default-source/coronaviruse/situation-reports/20200202-sitrep-13-ncov-v3.pdf
  • Zarocostas, J. (2020). How to fight an infodemic. The Lancet, 395(10225), 676. https://doi.org/10.1016/S0140-6736(20)30461-X
  • Zeng, J., & Schäfer, M. S. (2021). Conceptualizing ‘fake news’ in the digital age. New Media & Society, 23(1), 41–58. https://doi.org/10.1177/1461444820946450
Toplam 51 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular İletişim ve Medya Çalışmaları (Diğer)
Bölüm Makale
Yazarlar

Şeyma Filiz 0000-0002-5264-0857

Enes Bayraklı 0000-0002-5039-3493

Yayımlanma Tarihi 31 Ocak 2025
Gönderilme Tarihi 10 Aralık 2024
Kabul Tarihi 17 Ocak 2025
Yayımlandığı Sayı Yıl 2025

Kaynak Göster

APA Filiz, Ş., & Bayraklı, E. (2025). Avrupa Birliği’nin Dezenformasyonla Mücadele Stratejisi (2018-2024). TRT Akademi, 10(23), 10-41. https://doi.org/10.37679/trta.1599468