Kamuoyunun Dijital Tanıklığı: Uluslararası Haberlerde Gazze Üzerine Kullanıcı Söylemlerinin Duygu ve Konu Temelli Analizi

Öz

Bu çalışma, Gazze çatışmasına ilişkin uluslararası haber kanallarının YouTube’da yayımlanan videoları altındaki kullanıcı yorumlarını inceleyerek haber çerçevelemesi ile izleyici alımlaması arasındaki etkileşimi hesaplamalı sosyal bilimler yaklaşımıyla analiz etmektedir. Veri seti, “Gazze” anahtar kelimesini içeren ve yüksek izlenme oranına sahip 11 uluslararası haber kuruluşuna ait videolardan elde edilen kullanıcı yorumlarından oluşmaktadır. Yorumlar üzerinde BERT tabanlı duygu analizi, BERTopic konu modellemesi, kelime frekansı analizi, bigram analizi ve kelime birliktelik ağı gibi doğal dil işleme (NLP) yöntemleri uygulanmış; böylece dijital söylemin duygusal, insani ve politik bileşenleri çok katmanlı biçimde ortaya konmuştur. Bulgular, kullanıcı tepkilerinin büyük ölçüde negatif duygular, insani kayıplara odaklanmış değerlendirmeler, rehineler ve siviller etrafında şekillenen kriz temelli söylemler ile politik aktörlere ilişkin tartışmalarda yoğunlaştığını göstermektedir. Farklı haber kanallarının çatışmayı sunuş biçimleri, kullanıcı yorumlarında anlamlı söylemsel ayrışmalar üretmiş; görsel şiddet, yıkım düzeyi, trajedik hikâyeler ve politik çerçeveler yorumların duygusal tonunu belirgin biçimde etkilemiştir. Araştırma, hesaplamalı yöntemler kullanarak uluslararası haber içeriklerinin dijital ortamda duygusal kamuların oluşumunu nasıl yönlendirdiğini ortaya koymakta ve çatışma haberciliğinde çerçeveleme–alımlama ilişkisine veri temelli, özgün bir katkı sunmaktadır.

Anahtar Kelimeler

• Gazze
• Haber Çerçeveleme
• Dijital Kamuoyu
• Hesaplamalı Sosyal Bilimler
• Duygu Analizi
• Konu Modelleme

Public Opinion's Digital Testimony: Sentiment and Topic-Based Analysis of User Discourse on Gaza in International News

Öz

This study analyzes the interaction between news framing and audience reception using a computational social science approach by examining user comments under videos published on YouTube by international news channels related to the Gaza conflict. The dataset consists of user comments obtained from videos belonging to 11 international news organizations that contain the keyword “Gaza” and have high viewership rates. Natural language processing (NLP) methods such as BERT-based sentiment analysis, BERTopic topic modeling, word frequency analysis, bigram analysis, and word co-occurrence networks were applied to the comments, thus revealing the emotional, human, and political components of digital discourse in a multi-layered manner. The findings show that user reactions largely centered on negative emotions, assessments focused on human losses, crisis-based discourse shaped around hostages and civilians, and discussions about political actors. The ways in which different news channels presented the conflict produced meaningful discursive differences in user comments; visual violence, the level of destruction, tragic stories, and political frameworks significantly influenced the emotional tone of the comments. Using computational methods, the research reveals how international news content shapes the formation of emotional publics in the digital environment and offers a data-driven, original contribution to the framing–reception relationship in conflict journalism.

Anahtar Kelimeler

• Gaza
• News Framing
• Digital Public Opinion
• Computational Social Sciences
• Sentiment Analysis
• Topic Modeling

Kaynakça

1. Aday, S. (2016). Media, war, and public opinion. In Routledge Handbook of Media, Conflict and Security (pp. 126-137). Routledge.
2. Akpoghiran, I. P. (2023). News frames emotion: Analyzing how audience are influenced by news frames. American Journal of Arts, Social and Humanity Studies, 3(1), 48-64.
3. Al-Maghaireh, D. A., Shawish, N. S., Alsaqer, K., Kawafha, M., Sheyab, H. S., Al Mushasha, R. A., & Al Kofahi, A. (2024). Acute stress disorders among Jordanian adolescents after watching Gaza news footage on social media. Journal of Multidisciplinary Healthcare, 2521-2533.
4. Alaqad, M. H., Benelhadj, F., & Hashim, H. U. (2025). Framing Resistance: Western Discourse, Double Standards, and the Dehumanization of Palestinians. The International Journal of Palestine Studies, 1(1).
5. Alashqar, M. (2024). The role of language in framing the Israeli-Palestinian conflict on Twitter: The Escalation of Violence in Gaza in May 2021 as a Case Study. PhD diss., Ghent University.
6. Aljoundi, B. A. K. (2024). A Comparative Discourse Analysis of the lexical and ideological variations in the 2023 Palestinian-Israeli Conflict.
7. Alsaba, M. R. (2023). The Influence of The Abraham Accords on the Visual Coverage of the Israeli-Palestinian Conflict in Arab Media: A Comparative Analysis (Master’s thesis, The American University in Cairo (Egypt)).
8. Andersen, R., & De Silva, P. L. (Eds.). (2017). Routledge Companion to Media and Humanitarian Action. Routledge.

9. Balagurova, A. (2024). Visualising people in humanitarian crises: Where numbers meet empathy (Yayımlanmamış Yüksek Lisans tezi). Aalto Üniversitesi
10. Baum, M. A., & Potter, P. B. (2008). The relationships between mass media, public opinion, and foreign policy: Toward a theoretical synthesis. Annu. Rev. Polit. Sci., 11(1), 39-65.
11. Bishop, S. (2021). Influencer management tools: Algorithmic cultures, brand safety, and bias. Social media+ society, 7(1), 20563051211003066.
12. Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). Latent dirichlet allocation. Journal of machine Learning research, 3(Jan), 993-1022.
13. Blondel, V. D., Guillaume, J. L., Lambiotte, R., & Lefebvre, E. (2008). Fast unfolding of communities in large networks. Journal of statistical mechanics: theory and experiment, 2008(10), P10008.
14. Borah, P. (2011). Conceptual issues in framing theory: A systematic examination of a decade’s literature. Journal of communication, 61(2), 246-263.
15. Boumans, J. W., & Trilling, D. (2018). Taking stock of the toolkit: An overview of relevant automated content analysis approaches and techniques for digital journalism scholars. Rethinking research methods in an age of digital journalism, 8-23.
16. Boyacı Yıldırım, M. ve Yıldız, E. (2025). Hesaplamalı Sosyal Bilimler ve İletişim, Yeni Medya, Yapay Zekâ ve Veri Odaklı Yaklaşımlar. Nobel Bilimsel Eserler.
17. Boyd, D. (2010). Social network sites as networked publics: Affordances, dynamics, and implications. In A networked self (pp. 47-66). Routledge.
18. Boyd, D., & Crawford, K. (2012). Critical questions for big data: Provocations for a cultural, technological, and scholarly phenomenon. Information, communication & society, 15(5), 662-679.
19. Brantner, C., Lobinger, K., & Wetzstein, I. (2011). Effects of visual framing on emotional responses and evaluations of news stories about the Gaza conflict 2009. Journalism & Mass Communication Quarterly, 88(3), 523-540.
20. Brattoli, M. (2023). Framing the Israeli-Palestinian Conflict: A Corpus-Based Critical Discourse Analysis of News Articles on the Israeli-Palestinian War.
21. Bryman, A. (2016). Social research methods. Oxford University Press.
22. Bucher, T. (2018). If... then: Algorithmic power and politics. Oxford University Press.
23. Burgess, J., & Green, J. (2018). YouTube: Online video and participatory culture. John Wiley & Sons.
24. Butler, J. (2016). Frames of war: When is life grievable?. Verso Books.
25. Elmasry, M. H. (2025). Images of the Israel-Gaza war on Instagram: A content analysis of Western broadcast news posts. Journalism & Mass Communication Quarterly, 102(3), 695-721.
26. Canel, M., & Voltmer, K. (Eds.). (2014). Comparing political communication across time and space: New studies in an emerging field. Springer.
27. Chomsky, N. (1989). Political economy of the mass media. David Barsamian/Alternative Radio.
28. Chomsky, N., & Herman, E. (2002). A propaganda model. Manufacturing Consent: the Political Economy of the Mass Media. 2d ed. New York: Pantheon Books, 1-35.
29. Chouliaraki, L. (2006). The spectatorship of suffering.
30. Chouliaraki, L., Orwicz, M., & Greeley, R. (2019). The visual politics of the human. visual communication, 18(3), 301-309.
31. Cioffi-Revilla, C. (2014). Introduction to computational social science. Springer Verlag London Limited.
32. Dawson, P. (2020). Hashtag narrative: Emergent storytelling and affective publics in the digital age. International Journal of Cultural Studies, 23(6), 968-983.
33. De Vreese, C., Esser, F., & Hopmann, D. N. (Eds.). (2017). Comparing political journalism (p. 168). London: Routledge.
34. Devlin, J., Chang, M. W., Lee, K., & Toutanova, K. (2019). Bert: Pre-training of deep bidirectional transformers for language understanding. In Proceedings of the 2019 conference of the North American chapter of the association for computational linguistics: human language technologies, volume 1 (long and short papers) (pp. 4171-4186).
35. Dobernig, K., & Lobinger, K. (2010). Covering conflict: Differences in visual and verbal news coverage of the Gaza crisis 2009 in four weekly news media. Journal of Visual Literacy, 29(1), 88-105.
36. Duncombe, C. (2020). Social media and the visibility of horrific violence. International Affairs, 96(3), 609-629.
37. Edgerly, S., Vraga, E., Fung, T., Moon, T. J., Yoo, W. H., & Veenstra, A. (2009, October). YouTube as a public sphere: The proposition 8 debate. In Association of Internet Researchers Conference, Milwaukee, WI.
38. Elmasry, M. H. (2025). Images of the Israel-Gaza war on Instagram: A content analysis of Western broadcast news posts. Journalism & Mass Communication Quarterly, 102(3), 695-721.
39. Entman, R. M. (1993). Framing: Towards clarification of a fractured paradigm. McQuail’s reader in mass communication theory, 390, 397.
40. Etikan, I., Musa, S. A., & Alkassim, R. S. (2016). Comparison of convenience sampling and purposive sampling. American journal of theoretical and applied statistics, 5(1), 1-4.
41. Falk, R., & Friel, H. (2007). Israel-Palestine on Record: How the New York Times Misreports Conflict in the Middle East. Verso Books.
42. Fernández, L. (2021). Images that liberate: Moral shock and strategic visual communication in animal liberation activism. Journal of Communication Inquiry, 45(2), 138-158.
43. Gilboa, E. (2001). Diplomacy in the media age: Three models of uses and effects. Diplomacy and statecraft, 12(2), 1-28.
44. Goffman, E. (1974). Frame analysis: An essay on the organization of experience. Northeastern UP.
45. Graham, T., & Wright, S. (2015). A tale of two stories from “below the line”: Comment fields at the Guardian. The International Journal of Press/Politics, 20(3), 317-338.
46. Grimmer, J., Roberts, M. E., & Stewart, B. M. (2021). Machine learning for social science: An agnostic approach. Annual Review of Political Science, 24(1), 395-419.
47. Grootendorst, M. (2022). BERTopic: Neural topic modeling with a class-based TF-IDF procedure. arXiv preprint arXiv:2203.05794.
48. Güran, M. S., & Özarslan, H. (2022). Framing theory in the age of social media. Selçuk Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, (48), 446-457.
49. Hall, S. (1980). Encoding/decoding. In S. Hall, D. Hobson, A. Lowe, & P. Willis (Eds.), Culture, Media, Language (pp. 128–138). London, UK: Hutchinson University Library.
50. Halpern, D., & Gibbs, J. (2013). Social media as a catalyst for online deliberation? Exploring the affordances of Facebook and YouTube for political expression. Computers in human behavior, 29(3), 1159-1168.
51. Handley, R. L., & Ismail, A. (2010). Territory under siege:‘their’news,‘our’news and ‘ours both’news of the 2008 Gaza crisis. Media, War & Conflict, 3(3), 279-297.
52. Hautea, S., Parks, P., Takahashi, B., & Zeng, J. (2021). Showing They Care (Or Don’t): Affective Publics and Ambivalent Climate Activism on TikTok. Social Media and Society, 7 (2), 1-14.
53. Highfield, T. (2017). Social media and everyday politics. John Wiley & Sons. Hopwood, T. L., & Schutte, N. S (2017). Psychological outcomes in reaction to media exposure to disasters and large-scale violence: A meta-analysis. Psychology of violence, 7(2), 316.
54. Hurley, Z. (2025). Semiotic Study of the Gaza Conflict on Social Media. International Journal for the Semiotics of Law-Revue internationale de Sémiotique juridique, 1-20.
55. Jacobs, A. Z., & Wallach, H. (2021, March). Measurement and fairness. In Proceedings of the 2021 ACM conference on fairness, accountability, and transparency (pp. 375-385).
56. Jasper, J. M. (1998). The emotions of protest: Affective and reactive emotions in and around social movements. In Sociological forum (Vol. 13, No. 3, pp. 397-424). New York: Kluwer Academic Publishers Plenum Publishers.
57. Jasper, J. M. (2008). The art of moral protest: Culture, biography, and creativity in social movements. University of Chicago Press.
58. Jenkins, H. (2006). Convergence culture: Where old and new media collid. New York, NY: New, 1-2.
59. Juarez Miro, C. (2022). The comment gap: Affective publics and gatekeeping in The New York Times’ comment sections. Journalism, 23(4), 858-874.
60. Kapusta, J., Drlik, M., & Munk, M. (2021). Using of n-grams from morphological tags for fake news classification. PeerJ Computer Science, 7, e624.
61. Kennis, A. (2022). Digital-Age Resistance: Journalism, Social Movements and the Media Dependence Model. Routledge.
62. Kepplinger, H. M., Brosius, H. B., & Staab, J. F. (1991). Opinion formation in mediated conflicts and crises: a theory of cognitive–affective media effects. International Journal of Public Opinion Research, 3(2), 132-156.
63. Khalidi, R. (2020). The hundred years’ war on Palestine: A history of settler colonialism and resistance, 1917–2017. Metropolitan Books.
64. Khalili, L. (2007). Heroes and martyrs of Palestine: The politics of national commemoration (Vol. 27). Cambridge University Press.
65. Khan, Z. (2024). The Role of Media in Shaping Public Diplomacy. Journal Of Law, Social And Management Sciences, 3(1), 216-223.
66. Kozinets, R. V. (2015). Netnography: redefined. sage.
67. Ksiazek, T. B., Peer, L., & Lessard, K. (2016). User engagement with online news: Conceptualizing interactivity and exploring the relationship between online news videos and user comments. New media & society, 18(3), 502-520.
68. Kumar, D. (2012). Islamophobia and the Politics of Empire. Haymarket Books.
69. Kurasawa, F. (2013). The sentimentalist paradox: On the normative and visual foundations of humanitarianism. Journal of Global Ethics, 9(2), 201-214.
70. Kurasawa, F. (2015). How does humanitarian visuality work? A conceptual toolkit for a sociology of iconic suffering. Sociologica, 9(1), 0-0.
71. Kušen, E., & Strembeck, M. (2020). Emotional communication during crisis events: Mining structural OSN patterns. IEEE Internet Computing, 25(2), 58-65.
72. Lazer, D. M., Baum, M. A., Benkler, Y., Berinsky, A. J., Greenhill, K. M., Menczer, F.,... & Zittrain, J. L. (2018). The science of fake news. Science, 359(6380), 1094-1096.
73. Lazer, D. M., Pentland, A., Watts, D. J., Aral, S., Athey, S., Contractor, N., ... & Wagner, C. (2020). Computational social science: Obstacles and opportunities. Science, 369(6507), 1060-1062.
74. Lazer, D., Pentland, A., Adamic, L., Aral, S., Barabási, A. L., Brewer, D., ... & Van Alstyne, M. (2009). Computational social science. Science, 323(5915), 721-723.
75. Leaver, T., Highfield, T., & Abidin, C. (2020). Instagram: Visual social media cultures. John Wiley & Sons.
76. Lepekhin, M., & Sharoff, S. (2022). Estimating confidence of predictions of individual classifiers and their ensembles for the genre classification task. arXiv preprint arXiv:2206.07427.
77. Liu, Y., Ott, M., Goyal, N., Du, J., Joshi, M., Chen, D., ... & Stoyanov, V. (2019). Roberta: A robustly optimized bert pretraining approach. arXiv preprint arXiv:1907.11692.
78. Lünenborg, M. (2019). Affective publics. In Affective societies (pp. 319-329). Routledge.
79. Matthes, J. (2012). Framing politics: An integrative approach. American behavioral scientist, 56(3), 247-259.
80. Mayor, E., Miché, M., & Lieb, R. (2022). Associations between emotions expressed in internet news and subsequent emotional content on twitter. Heliyon, 8(12).
81. Nasar, W., Akhtar, N., & Anwar, M. N. (2025). Ideological Framing of the Palestine-Israel Conflict: A Corpus-Based Eco-Linguistic Analysis of Western and Middle Eastern Media Editorials. Social Science Review Archives, 3(2), 698-712.
82. Neuman, W. L. (2014). Social research methods: Qualitative and quantitative approaches (7th ed.). Pearson.
83. Papacharissi, Z. (2015). Affective publics: Sentiment, technology, and politics. Oxford University Press.
84. Papacharissi, Z. (2016). Affective publics and structures of storytelling: Sentiment, events and mediality. Information, communication & society, 19(3), 307-324.
85. Perloff, R. M. (2021). The dynamics of political communication: Media and politics in a digital age. Routledge.
86. Philo, G., & Berry, M. (2011). More bad news from Israel. Pluto Boo
87. Sahhar, M. E. (2015). Occupied Narrative: On Western Media Collusion with Israel’s’ wars’ and Recovering the Palestinian Story (Doctoral dissertation, University of Melbourne, School of Social and Political Sciences).
88. Said, E. (1978). Orientalism pantheon books. New York.
89. Salganik, M. J. (2019). Bit by bit: Social research in the digital age. Princeton University Press.
90. Scharkow, M., Mangold, F., Stier, S., & Breuer, J. (2020). How social network sites and other online intermediaries increase exposure to news. Proceedings of the National Academy of Sciences, 117(6), 2761-2763.
91. Seib, P. (2013). Transnational journalism, public diplomacy, and virtual states. In Foreign Correspondence (pp. 105-115). Routledge.
92. Sun, C., Qiu, X., Xu, Y., & Huang, X. (2019, October). How to fine-tune bert for text classification?. In China national conference on Chinese computational linguistics (pp. 194-206). Cham: Springer International Publishing.
93. Teddlie, C., & Yu, F. (2007). Mixed methods sampling: A typology with examples. Journal of mixed methods research, 1(1), 77-100.
94. Tenenboim-Weinblatt, K., & Baden, C. (2021). Gendered communication styles in the news: An algorithmic comparative study of conflict coverage. Communication research, 48(2), 233-256.
95. Van Atteveldt, W., Trilling, D., & Calderon, C. A. (2022). Computational analysis of communication. John Wiley & Sons.
96. Wang, Y., Liu, S., Afzal, N., Rastegar-Mojarad, M., Wang, L., Shen, F., ... & Liu, H. (2018). A comparison of word embeddings for the biomedical natural language processing. Journal of biomedical informatics, 87, 12-20.
97. Warshagha, A. Z., Ang, P. S., & Huan, C. (2024). Comparative Framing of the Palestinian-Israeli Conflict in Newspapers: An Analysis of Affect. GEMA Online Journal of Language Studies, 24(3).
98. Wicke, P., & Bolognesi, M. M. (2020). Framing COVID-19: How we conceptualize and discuss the pandemic on Twitter. PloS one, 15(9), e0240010.
99. Yemets, V. (2024). The Role of Media Diplomacy in Shaping the State’s International Image. Language, Culture, Politics. International Journal, 1(9), 133-145.
100. Yıldız, E., & Yıldırım, M. B. (2024). Sosyal Medyada Marka Boykotları ve Kriz İletişimi:‘Twitter (X)’Kullanıcı Yorumlarının Metin Madenciliği ile İncelenmesi. Etkileşim, (13), 286-313.
101. Yıldız, İ. (2025). Visualization of the Israeli-Palestinian War in Digital Media: An Analysis of Anadolu Agency Infographics. Filistin Araştırmaları Dergisi, (17), 129-166.
102. Yu, X., Haroon, M., Menchen-Trevino, E., & Wojcieszak, M. (2024). Nudging recommendation algorithms increases news consumption and diversity on YouTube. PNAS nexus, 3(12), pgae518.
103. Zaher, A. (2009). A critical discourse analysis of news reports on the Israeli/Palestinian conflict in selected Arab and western newspapers. Nottingham Trent University (United Kingdom).