SavedAdd your journal

Journals / Yönetim ve Ekonomi Araştırmaları Dergisi / 2026 / Cilt: 24 Sayı: 1

THE SENTIMENTAL FRAME OF THE MEDIA: ANALYZING THE NEWS HEADLINES ABOUT IMMIGRANTS AND REFUGEES IN ONLINE NEWS SOURCES THROUGH SENTIMENT ANALYSIS AND TOPIC MODELING

Merve Boyacı Yıldırım(İSTANBUL GELİŞİM ÜNİVERSİTESİ, İKTİSADİ, İDARİ VE SOSYAL BİLİMLER FAKÜLTESİ, HALKLA İLİŞKİLER VE TANITIM BÖLÜMÜ, HALKLA İLİŞKİLER VE TANITIM PR. (TAM BURSLU))0000-0003-2198-0733
Pages
46–66
Publication Date
2026-03-21
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The study uses computational social sciences to show that media content is both communicative and strategic, with social and political effects.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:This research examines the representation of immigrants and refugees in Türkiye's online news media through published news headlines.
📊
Key Findings & Data:At the end of 2024 and mid-2025, time series analysis shows increased negativity.
💡
Conclusion & Impact:The study uses computational social sciences to show that media content is both communicative and strategic, with social and political effects.
🔬Design:Modeling & Simulation
📍Scope:2024 Verileri
⚙️Variables:Immigrant · Refugee · Media Framing

Abstract

This research examines the representation of immigrants and refugees in Türkiye's online news media through published news headlines. A collection of headlines from four national news sources (TRT Haber, BirGün, Cumhuriyet, and Yeni Şafak) is examined using BERT-based sentiment analysis and BERTopic topic modeling. Negative feelings dominate news headlines across all media venues, while positive depictions are scarce. At the end of 2024 and mid-2025, time series analysis shows increased negativity. Topic modeling revealed border crossings, security, illegal immigration, mass deportation, and refugee discourses tied to national policy. Word cloud and co-occurring word pair studies show that "migrant caught", "irregular migrant", "detained”, "migrant smuggling" and "illegal" are frequently repeated. These discursive tendencies show that immigration is mostly framed as a security danger and control issue. The study uses computational social sciences to show that media content is both communicative and strategic, with social and political effects.

Özet

This research examines the representation of immigrants and refugees in Türkiye's online news media through published news headlines. A collection of headlines from four national news sources (TRT Haber, BirGün, Cumhuriyet, and Yeni Şafak) is examined using BERT-based sentiment analysis and BERTopic topic modeling. Negative feelings dominate news headlines across all media venues, while positive depictions are scarce. At the end of 2024 and mid-2025, time series analysis shows increased negativity. Topic modeling revealed border crossings, security, illegal immigration, mass deportation, and refugee discourses tied to national policy. Word cloud and co-occurring word pair studies show that "migrant caught", "irregular migrant", "detained”, "migrant smuggling" and "illegal" are frequently repeated. These discursive tendencies show that immigration is mostly framed as a security danger and control issue. The study uses computational social sciences to show that media content is both communicative and strategic, with social and political effects.

🔖

Cite This Article

Yıldırım, M. B. (2026). THE SENTIMENTAL FRAME OF THE MEDIA: ANALYZING THE NEWS HEADLINES ABOUT IMMIGRANTS AND REFUGEES IN ONLINE NEWS SOURCES THROUGH SENTIMENT ANALYSIS AND TOPIC MODELING. Yönetim ve Ekonomi Araştırmaları Dergisi, Cilt: 24 Sayı: 1, 46–66. https://doi.org/10.11611/yead.1751799

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (56)

  1. Ala, T. and Uğuz, S. (2021) "Türkiye’de bölgesel kalkınmanın girişimcilik, inovasyon ve ar-ge çalışmalarıyla ilişkisinin bibliyometrik analizi ve LDA MALLET uygulaması", Erzincan Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 14(20): 13–29. https://doi.org/10.46790/erzisosbil.968808.
  2. Angelov, D. (2020) "Top2vec: Distributed representations of topics", arXiv preprint, arXiv:2008.09470.
  3. Bauman, Z. (2019) “Kapımızdaki Yabancılar” (E. Barca, Trans.), İstanbul: Ayrıntı Yayınları.
  4. Benson, R. (2013) “Shaping Immigration News: A French American Comparison”, Cambridge: Cambridge University Press.
  5. Berry, M., Garcia-Blanco, I. and Moore, K. (2016) “Press coverage of the refugee and migrant crisis in the EU: A content analysis of five European countries”. [Project Report]. Geneva: United Nations High Commissioner for Refugees. Available at: http://www.unhcr.org/56bb369c9.html
  6. Blei, D. M., Ng, A. Y. and Jordan, M. I. (2003) "Latent Dirichlet Allocation", Journal of Machine Learning Research, 3: 993–1022.
  7. Boomgaarden, H. G. and Vliegenthart, R. (2009) "How News Content Influences Anti-Immigration Attitudes: Germany, 1993–2005", European Journal of Political Research, 48(4): 516–542. https://doi.org/10.1111/j.1475-6765.2009.01831.x
  8. Boyacı Yıldırım, M. and Özgen, E. (2024) "Dijitalleşme ekseninde infodemi ve bilgi düzensizlikleri", Akademik Hassasiyetler, 11(25): 500–529. https://doi.org/10.58884/akademik-hassasiyetler.1435823
  9. Bozdag, U. (2024). “Framing displaced persons: An analysis of Turkish media’s use of migration metaphors on Twitter. Intersections.” East European Journal of Society and Politics, 10(1). https://doi.org/10.17356/ieejsp.v10i1.1189
  10. Cangöz, İ. and Wakili, J. (2022) "Gazetelerin İnternet Sitelerinde Afgan Göçmenlerin Temsili", Galatasaray Üniversitesi İletişim Dergisi, (36): 34–60. https://doi.org/10.16878/gsuilet.1086587
  11. Caporusso, J., Hoogland, D., Brglez, M., Koloski, B., Purver, M. and Pollak, S. (2024) "A Computational Analysis of the Dehumanisation of Migrants from Syria and Ukraine in Slovene News Media", arXiv preprint, arXiv:2404.07036.
  12. Castles, S., de Haas, H. and Miller, M. J. (2014) “The Age of Migration: International Population Movements in the Modern World”, London: Palgrave Macmillan.
  13. Çakıcı, Z. (2024) “Türk Basınında Düzensiz Göçün Görsel Temsili: Taliban Yönetimi Sonrası Afgan Göçü”, Unpublished PhD Dissertation, Galatasaray University, Institute of Social Sciences, Istanbul.
  14. Çakır, C. and Köseliören, M. (2022) "Medyada Metaforik Temsil: Göçmenler Üzerine Bir Çalışma", Sosyal Mucit Academic Review, 3(2): 237–262. https://doi.org/10.54733/smar.1166676
  15. Devlin, J., Chang, M. W., Lee, K. and Toutanova, K. (2019) "BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding", Proceedings of NAACL-HLT: 4171–4186. https://doi.org/10.48550/arXiv.1810.04805
  16. Doğanay, Ü. and Çoban Keneş, H. (2016) "Yazılı Basında Suriyeli ‘Mülteciler’: Ayrımcı Söylemlerin Rasyonel ve Duygusal Gerekçelerinin İnşası", Mülkiye Dergisi, 40(1): 143–184.
  17. Eberl, J. M., Meltzer, C. E., Heidenreich, T., Herrero, B., Theorin, N., Lind, F. and Strömbäck, J. (2018) "The European Media Discourse on Immigration and Its Effects: A Literature Review", Annals of the ICA, 42(3): 207–223. https://doi.org/10.1080/23808985.2018.1497452
  18. Erdoğan, M. (2017) “Türkiye’deki Suriyeliler: Toplumsal Kabul ve Uyum”, Ankara: HUGO.
  19. Erol, H. and Yaylacı, F. G. (2022) "Türkiye’deki Afgan Sığınmacılar ve Medya Temsilleri Bağlamında Görüşleri", Göç Dergisi, 9(2): 181–206.
  20. Esses, V. M., Medianu, S. and Lawson, A. S. (2013) "Uncertainty, Threat, and the Role of the Media in Promoting the Dehumanization of Immigrants and Refugees", Journal of Social Issues, 69(3): 518–536. https://doi.org/10.1111/josi.12027
  21. Fairclough, N. (1995) “Media Discourse”, London: Edward Arnold.
  22. Gezik, Z. (2022) "Suriyeli Göçmenlerin Anaakım Medyada Temsili", İletişim Bilimi Araştırmaları Dergisi, 2(2): 135–153. https://doi.org/10.7456/100202100/005
  23. Greussing, E. and Boomgaarden, H. G. (2017) “Shifting the refugee narrative? An automated frame analysis of Europe’s 2015 refugee crisis.” Journal of ethnic and migration studies, 43(11), 1749-1774.
  24. Grootendorst, M. (2022) "BERTopic: Neural Topic Modeling with a Class-Based TF-IDF Procedure", arXiv preprint, arXiv:2203.05794.
  25. Heidenreich, T., Lind, F., Eberl, J. M. and Boomgaarden, H. G. (2019) “Media framing dynamics of the ‘European refugee crisis’: A comparative topic modelling approach”. Journal of Refugee Studies, 32(Special_Issue_1), i172-i182.
  26. Ibrahim, M. (2005) "The Securitization of Migration: A Racial Discourse", International Migration, 43(5): 163–187. https://doi.org/10.1111/j.1468-2435.2005.00345.x
  27. International Organization for Migration- IOM (2009) “Glossary on Migration”, Geneva: IOM Publishing. Karpat, K. H. (2010) “Osmanlı'dan Günümüze Etnik Yapılanma ve Göçler”, İstanbul: Timaş Yayınları.
  28. Keskin, S. and Kömür, G. (2023) "Türkiye’ye Yönelik Genç Erkek Yoğunluklu Afgan Göç Dalgasının Irkçı Söylemler Üzerindeki Etkisi", Türk ve İslam Dünyası Sosyal Araştırmalar Dergisi, 10(38): 32–53. https://doi.org/10.29228/TIDSAD.72561
  29. Klocker, N. and Dunn, K. M. (2003). “Who's driving the asylum debate? Newspaper and government representations of asylum seekers.” Media International Australia, 109(1), 71-92. https://doi.org/10.1177/1329878X0310900109
  30. Livberber, T. (2021) "Suriyeli Sığınmacıların Türk Basınında Temsili: Haberler Üzerine Eleştirel Bir Analiz", İstanbul Aydın Üniversitesi Sosyal Bilimler Dergisi, 13(4): 1003–1028.
  31. Lortoğlu, C. (2019) “Beklenmeyen Misafir: Suriyeli Mültecilerin Medyada Temsili”, Unpublished Master’s Thesis, Marmara University, Istanbul.
  32. Lynn, N., and Lea, S. (2003) “A phantom menace and the new Apartheid': the social construction of asylum-seekers in the United Kingdom”, Discourse & Society, 14(4), 425-452. https://doi.org/10.1177/0957926503014004002
  33. Manap, Ç. (2025) "Sosyal Medyada Mülteci Temsilinin Söylem Analizi: Ekşi Sözlük Örneği", Pamukkale Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, (67): 83–99. https://doi.org/10.30794/pausbed.1509785
  34. Nedungadi, P., Veena, G., Tang, K.-Y., Menon, R. R. K. and Raman, R. (2025) "AI Techniques and Applications for Online Social Networks and Media: Insights From BERTopic Modeling", IEEE Access, 13: 37389–37407. https://doi.org/10.1109/ACCESS.2025.3543795
  35. Ogan, C., Willnat, L., Pennington, R. and Bashir, M. (2014) "The Rise of Anti-Muslim Prejudice: Media and Islamophobia in Europe and the United States", International Communication Gazette, 76(1): 27–46. https://doi.org/10.1177/1748048513504048
  36. Pandır, M., Efe, İ. and Paksoy, A. F. (2015) “Türk Basınında Suriyeli Sığınmacı Temsili Üzerine Bir İçerik Analizi/A Content Analysis on the Representation of Syrian Asylum Seekers in the Turkish Press”, Marmara İletişim Dergisi, (24), 1-26.
  37. Petersen, W. (1958) "A General Typology of Migration", American Sociological Review, 23(3): 256–266. https://doi.org/10.2307/2089239
  38. Raman, R., Pattnaik, D., Hughes, L. and Nedungadi, P. (2024) "Unveiling the Dynamics of AI Applications: A Review of Reviews Using Scientometrics and BERTopic Modeling", Journal of Innovation & Knowledge, 9(3): 100517. https://doi.org/10.1016/j.jik.2024.100517
  39. Richmond, A. H. (1988) "Sociological Theories of International Migration: The Case of Refugees", Current Sociology, 36(2): 7–25. https://doi.org/10.1177/001139288036002004
  40. Rogers, A., Kovaleva, O. and Rumshisky, A. (2021) "A Primer in BERTology: What We Know About How BERT Works", TACL, 8: 842–866. https://doi.org/10.48550/arXiv.2002.12327
  41. Sanner, M. F. (1999) "Python: A Programming Language for Software Integration and Development", Journal of Molecular Graphics and Modelling, 17(1): 57–61.
  42. Sellam, T., Das, D. and Parikh, A. P. (2020) "BLEURT: Learning Robust Metrics for Text Generation", arXiv preprint, arXiv:2004.04696.
  43. Sun, C., Qiu, X., Xu, Y. and Huang, X. (2019) "How to Fine-tune BERT for Text Classification?", China National Conference on Chinese Computational Linguistics: 194–206. https://doi.org/10.1007/978-3-030-32381-3_16 Taşcı, F. (2009) "Bir Sosyal Politika Sorunu Olarak Göç", Kamu-İş Dergisi, 10(4): 177–204.
  44. Tiryaki, S. (2022) "Türk Basınında Göçmen, Sığınmacı ve Mülteci Haberleri Üzerine Bir İnceleme", Kültür Araştırmaları Dergisi, (15): 124–156. https://doi.org/10.46250/kulturder.118889
  45. Turkish Language Association (n.d.) Turkish Language Dictionary, https://sozluk.gov.tr/ (02.07.2025). Uçak, O. (2017) "Göç Hareketleri ve Medyada Göçmen Haberleri", Yeni Medya Elektronik Dergisi, 1(3): 242–254.
  46. United Nations- UN (1951) “The 1951 Refugee Convention”, Available at: https://www.unhcr.org/about-unhcr/overview/1951-refugee-convention (05.07.2025).
  47. United Nations High Commissioner for Refugees -UNHCR (2010) “Convention Relating to the Status of Refugees: Text of the 1951 Convention, Text of the 1967 Protocol and Introductory Note”, Geneva: United Nations High Commissioner for Refugees. Available at: https://www.unhcr.org/sites/default/files/2025-02/1951-refugee-convention-1967-protocol.pdf
  48. Van Dijk, T. (1988) “News as Discourse”, London: Lawrence Erlbaum Associates.
  49. Van Dijk, T. A. (2000) "New(s) Racism: A Discourse Analytical Approach", Ethnic Minorities and the Media: 33–49.
  50. Van Gorp, B. (2005) "Where is the Frame? Victims and Intruders in the Belgian Press Coverage of the Asylum Issue", European Journal of Communication, 20(4): 484–507. https://doi.org/10.1177/0267323105058253
  51. Vollmer, B. and Karakayali, S. (2018) "The Volatility of the Discourse on Refugees in Germany", Journal of Immigrant & Refugee Studies, 16(1–2): 118–139. https://doi.org/10.1080/15562948.2017.1288284
  52. Wang, A., Singh, A., Michael, J., Hill, F., Levy, O. and Bowman, S. R. (2018) "GLUE: A Multi-task Benchmark and Analysis Platform for Natural Language Understanding", arXiv preprint, arXiv:1804.07461.
  53. Wang, Z., Chen, J., Chen, J. and Chen, H. (2024) "Identifying Interdisciplinary Topics and Their Evolu tion Based on BERTopic", Scientometrics, 129: 7359–7384. https://doi.org/10.1007/s11192-023-04776-5
  54. Wodak, R. (2015) “The Politics of Fear: What Right-wing Populist Discourses Mean”, London: Sage. Yalçın, C. (2004) “Göç Sosyolojisi”, Ankara: Anı Yayıncılık.
  55. Yıldız, E. and Yıldırım, M. B. (2024) "Sosyal Medyada Marka Boykotları ve Kriz İletişimi: ‘Twitter (X)’ Kullanıcı Yorumlarının Metin Madenciliği ile İncelenmesi", Etkileşim, (13): 286–313. https://doi.org/10.32739/etkilesim.2024.7.13.249
  56. Zhang, T., Kishore, V., Wu, F., Weinberger, K. Q. and Artzi, Y. (2019) "BERTScore: Evaluating Text Generation with BERT", arXiv preprint, arXiv:1904.09675