Exploring Reflections of the 2023 Kahramanmaraş Earthquake on X: A Computational Study on Türkiye and Syria

Yıl 2025, Cilt: 20 Sayı: 1, 143 - 171

Sadettin Demirel , Zindan Çakıcı , Neslihan Bulur

https://doi.org/10.17550/akademikincelemeler.1593038

Öz

Earthquakes are multidimensional phenomena that disrupt socio-structural systems and erode collective resilience frameworks. Social media acts as a vital platform for information dissemination and communication within such contexts. The Kahramanmaraş earthquakes of February 6, 2023, induced significant physical and demographic consequences across Türkiye and Syria. A review of existing literature indicates a disproportionate emphasis on Türkiye within communication studies, with minimal attention to Syria or comparative analyses between the two nations. This study conducts a comparative analysis of social media discourse on the February 6, 2023, earthquakes in Türkiye and Syria. Employing computational techniques, including sentiment analysis, textual analysis, and network analysis, over 256,227 tweets were examined to identify dominant themes, linguistic patterns, and sentiment polarity shifts. The analysis reveals distinct differences in social media reflections of Türkiye and Syria. Discourse on Türkiye primarily addressed rescue operations and infrastructural damage, while content on Syria centered on humanitarian crises and political constraints affecting disaster response. Posts related to Syria exhibited a higher proportion of negative sentiment. This research contributed an empirical framework for examining the dynamics of public discourse during earthquake crises and clarifies the interrelationship between social media narratives and socio-political structures in contexts characterized by fragile state.

Anahtar Kelimeler

Social Media, Kahramanmaraş Earthquake, X, Computational Techniques, Fragile State

2023 Kahramanmaraş Depreminin X'teki Yansımalarının İncelenmesi: Türkiye ve Suriye Üzerine Bir Hesaplamalı Çalışma

Öz

Depremler, fiziksel yıkımın ötesinde, toplumsal bağları zayıflatarak sosyal dayanışmayı ve kolektif direnci derinden sarsan çok boyutlu krizlerdir. Sosyal medya ise bu süreçte etkin ve belirleyici bir role sahiptir. 6 Şubat 2023 Kahramanmaraş depremi de hem Türkiye’yi hem de Suriye’yi hem fiziksel hem de beşeri açıdan ciddi boyutlarda etkilemiştir. Literatür incelendiğinde, bu depremin iletişim bilimleri perspektifinden Türkiye bağlamında daha fazla çalışıldığı, Suriye’deki yıkımı bu perspektiften inceleyen veya iki ülkeyi karşılaştırmalı olarak inceleyen çalışmaların yok denecek kadar az olduğu görülmüştür. Bu çalışma da 6 Şubat 2023 Kahramanmaraş depremlerinin X yansımalarını Türkiye ve Suriye bağlamında karşılaştırmalı olarak analiz etmeyi amaçlamaktadır. Bu da çalışmanın özgün yönünü ortaya koymaktadır. Araştırma kapsamında, 250 binden fazla tweet üzerinde duygu analizi, metin analizi ve ağ analizi gibi hesaplamalı yöntemler kullanılarak iki ülkeye yönelik sosyal medya içeriklerinde öne çıkan temalar, ifadeler ve gönderilerin polaritesi incelenmiştir. Çalışma, hem deprem sonrası kamuoyu algısındaki farklılıkları hem de kırılgan devletlerin medya yansımaları üzerindeki etkilerini anlamaya katkıda bulunmayı hedeflemektedir. Bulgularda, Türkiye ve Suriye’ye yönelik paylaşımlardaki bağlamların farklılaştığı gözlemlenmiştir. Türkiye bağlamında kullanılan kelimelerin daha çok kurtarma operasyonları ve yıkımın boyutlarına odaklanırken, Suriye’ye ilişkin paylaşımların ise insani kriz ve politik engellere yönelik olduğu ve bu paylaşımlarda olumsuz polaritenin daha hakim olduğu tespit edilmiştir.

Anahtar Kelimeler

Sosyal Medya, Kahramanmaraş Depremi, X, Hesaplamalı Teknikler, Kırılgan Devlet

Kaynakça

• Ağın-Gözükızıl, C., & Tezcan, S. (2023). Cumhuriyet’in yüzüncü yılında Türkiye’de afetler: 06 Şubat 2023 Kahramanmaraş depremi. Kent Akademisi, 16 (Türkiye Cumhuriyeti’nin 100. Yılı Özel Sayısı), 97-114. https://doi.org/10.35674/kent.1353445
• Alfuqaha, O. A., Al-Masarwah, U. M., Farah, R. I., Yasin, J. A., Alkuttob, L. A., Muslieh, N. I., ... & Alshubbak, N. A. H. (2023). The impact of Turkey and Syria earthquakes on university students: Posttraumatic stress disorder symptoms, meaning in life, and social support. Behavioral Sciences, 13(7), 587. https://doi.org/10.3390/bs13070587
• Amiresmaili, M., Zolala, F., Nekoei-Moghadam, M., Salavatian, S., Chashmyazdan, M., Soltani, A., & Savabi, J. (2021). Role of social media in earthquake: A systematic review. Iran. Red. Crescent Med. J, 23(5), 1-8. https://doi.org/10.32592/ircmj.2021.23.5.447
• Aryal, K. (2023). Media representation: Coverage of the Nepali army’s rescue and relief operations. Unity Journal, 4(01), 345-354. https://doi.org/10.3126/unityj.v4i01.52250
• Ata, F. (2023). Afet haberciliği: Kahramanmaraş merkezli depremler sürecinde sosyal medyaya yönelik bir değerlendirme. TRT Akademi, 8(18), 606-629. https://doi.org/10.37679/trta.1271366
• Atalay, G. E., & Muratoğlu Pehlivan, B. (2024). Aestheticizing the pain: A critical analysis of media representation of earthquake victim children in Turkey. Sociology Lens, 37(1), 116-130. https://doi.org/10.1111/johs.12437
• Atan, S., & Çınar, Y. (2019). Borsa İstanbul’da finansal haberler ile piyasa değeri ilişkisinin metin madenciliği ve duygu (sentiment) analizi ile incelenmesi. Ankara Üniversitesi SBF Dergisi, 74(1), 1–34. https://doi.org/10.33630/ausbf.523199
• Aydın, A. F. (2023). Sosyal medyada dezenformasyon ve manipülasyon: 2023 Kahramanmaraş depremi örneği. İnsan ve Toplum Bilimleri Araştırmaları Dergisi, 12(5), 2603-2624. https://doi.org/10.15869/itobiad.1283358
• Bakkour, S., & Sahtout, R. (2023). The dimensions and attributes of state failure in Syria. Journal of Balkan and Near Eastern Studies, 25(6), 1020-1036. https://doi.org/10.1080/19448953.2023.2167337
• Barrie, C., & Ho, J. (2021). academictwitteR: An R package to access the Twitter Academic Research Product Track v2 API endpoint. Journal of Open Source Software, 6(62), 3272. https://doi.org/10.21105/joss.03272
• Basmacı, G. (2023). Use of children’s photos in natural disaster news: The example of Kahramanmaraş earthquake. International Journal of Social and Humanities Sciences, 7(3), 135-148. https://dergipark.org.tr/en/pub/ijshs/issue/82714/1419476
• Bauman, Z. (2013). Liquid fear. John Wiley & Sons.
• Beck, U. (2011). Risk toplumu: Başka bir modernliğe doğru (K. Özdoğan & B. Doğan, Çev.). İthaki Yayınları.
• Beck, U. (1992). Risk society: Towards a new modernity. Sage Publications.
• Benoit, K. (2020). Text as data: An overview. In Luigi Curini & R. Franzese (Eds.), The SAGE Handbook of research methods in political science and international relations. SAGE Publications Ltd. https://methods.sagepub.com/book/research-methods-in-political-science-and-international-relations
• Benoit, K., Watanabe, K., Wang, H., Nulty, P., Obeng, A., Müller, S., & Matsuo, A. (2018). quanteda: An R package for the quantitative analysis of textual data. Journal of Open Source Software, 3(30), 774. https://doi.org/10.21105/joss.00774
• Bird, S., Klein, E., & Loper, E. (2009). Natural language processing with Python. O’Reilly.
• Bondi, M. (2010). Perspectives on keywords and keyness: An introduction. In M. Bondi & M. Scott (Eds.), studies in corpus linguistics (Vol. 41, pp. 1–18). John Benjamins Publishing Company. https://doi.org/10.1075/scl.41.01bon
• Bossu, R., Corradini, M., Cheny, J.-M., & Fallou, L. (2023). A social bot in support of crisis communication: 10-years of @LastQuake experience on Twitter. Frontiers in Communication, 8(0), 1-10. https://doi.org/10.3389/fcomm.2023.992654
• Çakıcı, Z. (2024). Türk basınında düzensiz göçün görsel temsili: Taliban yönetimi sonrası Afgan göçü [Yayımlanmamış Doktora tezi, Galatasaray Üniversitesi].
• Çakıcı, Z., & Meriç, E. (2024). Exploring United Nations High Commissioner for Refugees' (UNHCR) TikTok landscape: Insights into migration representations. In S. Kir Elitaş (Ed.), Media representation of migrants and refugees (pp. 278-295). IGI Global.
• Çakıcı, Z. (2024). Cyberstalking practices among youth in Türkiye: Motivational drivers, digital avenues, and perceptual paradigms. Türkiye İletişim Araştırmaları Dergisi (46), 1-22. https://doi.org/10.17829/turcom.1488278
• Camacho-Collados, J., Rezaee, K., Riahi, T., Ushio, A., Loureiro, D., Antypas, D., Boisson, J., Espinosa-Anke, L., Liu, F., Martínez-Cámara, E., Medina, G., Buhrmann, T., Neves, L., & Barbieri, F. (2022). TweetNLP: Cutting-Edge natural language processing for social media (arXiv:2206.14774). arXiv. http://arxiv.org/abs/2206.14774
• Correa, T., Scherman, A., & Arriagada, A. (2016). Audiences and disasters: Analyses of media diaries before and after an earthquake and a massive fire: Audiences and disasters. Journal of Communication, 66(4), 519-541. https://doi.org/10.1111/jcom.12245
• Demirel, S. (2024). Sosyal Medya ve Aktif Kullanıcı. Eğitim Yayınevi.
• Demirel, S., Kahraman-Gokalp, E., & Gündüz, U. (2024). From optimism to concern: Unveiling sentiments and perceptions surrounding ChatGPT on Twitter. International Journal of Human–Computer Interaction, 1–23. https://doi.org/10.1080/10447318.2024.2392964
• Demirel, S., Bulur, N., & Çakıcı, Z. (2024). Utilizing artificial intelligence for text classification in communication sciences: Reliability of ChatGPT models in Turkish texts. In D. Darwish (Ed.), Design and development of emerging chatbot technology (pp. 218-235). IGI Global Scientific Publishing. https://doi.org/10.4018/979-8-3693-1830-0.ch013
• Demirel, Y., & İcil Tuncer, A. (2024). Türkiye’nin itibarı güçlü şirketlerinin ulusal yas dönemindeki sosyal medya paylaşımlarının değerlendirilmesi. Pamukkale Üniversitesi İletişim Bilimleri Dergisi, 3(1), 1-23. https://dergipark.org.tr/tr/pub/pauibd/issue/85587/1407598
• Demirhan, K. (2024). Kahramanmaraş depremlerinden sonra Twitter etiketlerinin kriz yönetimi bağlamında analizi. Akademik Yaklaşımlar Dergisi, 15(1 -Deprem Özel Sayısı-), 430-454. https://doi.org/10.54688/ayd.1412222
• Demirhan, T., & Hacıoğlu, İ. (2024). 6 Şubat 2023 Türkiye’deki deprem fırtınasının X özelinde tanımlayıcı analizlerinin yapılması. Fırat Üniversitesi Sosyal Bilimler Dergisi, 34(1), 285-300. https://doi.org/10.18069/firatsbed.1384400
• Devlin, J., Chang, M.-W., Lee, K., & Toutanova, K. (2019). BERT: Pre-training of deep bidirectional transformers for language understanding (arXiv:1810.04805). arXiv. http://arxiv.org/abs/1810.04805
• Dyvik, E. (2024). The most spoken languages worldwide 2023. Statista. https://www.statista.com/statistics/266808/the-most-spoken-languages-worldwide/
• Eldem Anar, Ü. İ. (2021). Sosyal medya ortamında yer alan afet haberlerinde etkileşim; İzmir depremi örneği. Turkish Online Journal of Design Art and Communication, 11(3), 1129-1147.
• Eryürük, F. T., Odabaşı, F., & Eryürük, H. (2024). Social media use of higher education students in the earthquake disaster. Yükseköğretim Dergisi, 14(2), 37-44. https://doi.org/10.53478/yuksekogretim.1312375
• Ewelie, C., & Nwaorgu, O. C. (2021). State fragility and humanitarian crisis in Syria. International Journal of Research and Innovation in Social Science, 5(6), 313-318.
• Fallou, L., Bossu, R., & Cheny, J.-M. (2024). Prebunking earthquake predictions on social media. Frontiers in Communication, 9, 1-10. https://doi.org/10.3389/fcomm.2024.1391480
• Fokaefs, A., & Sapountzaki, K. (2021). Crisis communication after earthquakes in Greece and Japan: Effects on seismic disaster management. Sustainability, 13(16), 9257. https://doi.org/10.3390/su13169257
• Gezici, G., & Yanıkoğlu, B. (2018). Sentiment analysis in Turkish. In Turkish Natural Language Processing (pp. 255–271). Springer.
• Gökmen, E. (2023). A study on the appearance of the Kahramanmaraş earthquake on social media. OPUS Journal of Society Research, 20(55), 576-591. https://doi.org/10.26466/opusjsr.1347043
• Göksel, P., Usta, M. B., & Böke, Ö. (2024). The effect of media exposure of the 2023 Kahramanmaras earthquake on traumatic stress. Journal of Experimental and Clinical Medicine, 41(1), 132-137. https://dergipark.org.tr/en/pub/omujecm/issue/83825/1406308#article_cite
• Greenberg, J., & Scanlon, T. J. (2016). Old media, new media, and the complex story of disasters. Içinde J. Greenberg & T. J. Scanlon, Oxford research encyclopedia of natural hazard science. Oxford University Press. https://doi.org/10.1093/acrefore/9780199389407.013.21
• Grimmer, J., & Stewart, B. M. (2013). Text as data: The promise and pitfalls of automatic content analysis methods for political texts. Political Analysis, 21(3), 267–297. Cambridge Core. https://doi.org/10.1093/pan/mps028
• Gündüz, U., & Demirel, S. (2023). Metaverse-related perceptions and sentiments on Twitter: Evidence from text mining and network analysis. Electronic Commerce Research. https://doi.org/10.1007/s10660-023-09745-x
• IOM (2023). Türkiye ve Suriye 2023 depremleri-destek faaliyetleri. Erişim: https://turkiye.iom.int/sites/g/files/tmzbdl1061/files/documents/2023-08/iom-turkiye-syria-earthquake-response-update_19-march-2023-tr.pdf
• IOM (International Organization for Migration). (2023). Türkiye and Syria 2023 earthquakes – Response update. https://turkiye.iom.int/sites/g/files/tmzbdl1061/files/documents/2023-07/_web_iom-turkiye-syria-earthquake-response-update_18-july-2023.pdf
• Jo,Taeho. (2019). Text mining—concepts, implementation, and big data challenge (1st ed.). Springer, Cham.
• Kahraman-Gokalp, E., Demirel, S., & Gündüz, U. (2024). Exploring the surge of negativity during the COVID-19 pandemic: Computational text and sentiment analysis across eight newsrooms’ tweets. Atlantic Journal of Communication, 32(2), 298–324. https://doi.org/10.1080/15456870.2023.2293169
• Kayıhan, B. (2024). Disaster journalism through a political economy framework: An analysis of the Turkish press coverage of the 2023 Kahramanmaraş earthquakes. Sociology Lens, 37(3), 348-370. https://doi.org/10.1111/johs.12462
• Keykhaei, M., Samany, N. N., Jelokhani-Niaraki, M., & Zlatanova, S. (2023). A situation-aware emergency evacuation (SAEE) model using multi-agent-based simulation for crisis management after earthquake warning. Geo-Spatial Information Science, 1-24. https://doi.org/10.1080/10095020.2023.2270017
• Khoo, C. S., & Johnkhan, S. B. (2018). Lexicon-based sentiment analysis: Comparative evaluation of six sentiment lexicons. Journal of Information Science, 44(4), 491–511. https://doi.org/10.1177/0165551517703514
• Kirazoluğu, O. (2024). Proximity as a news value: A quantitative analysis of February 2023 Türkiye earthquakes news in international media. Gümüşhane Üniversitesi Sosyal Bilimler Dergisi, 15(3), 662-675.
• Koçyiğit, A. (2024). Afet ve kriz dönemlerinde bireylerin sosyal medya kullanım pratikleri ve infobezite: Kahramanmaraş depremi örneği. Gümüşhane Üniversitesi İletişim Fakültesi Elektronik Dergisi, 12(1), 62-87. https://doi.org/10.19145/e-gifder.1406261
• Kwanda, F. A., & Lin, T. T. C. (2020). Fake news practices in Indonesian newsrooms during and after the Palu earthquake: A hierarchy-of-influences approach. Information, Communication & Society, 23(6), 849-866. https://doi.org/10.1080/1369118X.2020.1759669
• Liu, B. (2020). Sentiment analysis mining opinions, sentiments, and emotions (2nd ed.). Cambridge University Press.
• Liu, Y., Ott, M., Goyal, N., Du, J., Joshi, M., Chen, D., Levy, O., Lewis, M., Zettlemoyer, L., & Stoyanov, V. (2019). RoBERTa: A robustly optimized bert pretraining approach (arXiv:1907.11692). arXiv. http://arxiv.org/abs/1907.11692
• Maden, S. (2023). 6 Şubat 2023’te Kahramanmaraş’ta yaşanan depremler ekseninde Türkiye’de deprem haberciliğine bakış: Prof. Dr. Süleyman İrvan ile söyleşi. Etkileşim (11), 406-420. https://doi.org/10.32739/etkilesim.2023.6.11.202
• Mahbubur Rahman, M., Sadequr Rahman, M., & Jerin, T. (2023). Social vulnerability to earthquake disaster: Insights from the people of 48th ward of Dhaka South City, Bangladesh. Environmental Hazards, 22(2), 116-135. https://doi.org/10.1080/17477891.2022.2085075
• Meriç, E. & Çakıcı, Z. (2024). From TikTok trends to pandemic essentials: A comparative analysis of the World Health Organization's health communication strategies on TikTok. In H. Gürkan & A. Serttaş (Eds.), Transformed communication codes in the mediated world: A contemporary perspective (pp. 1-23). IGI Global Scientific Publishing. https://doi.org/10.4018/979-8-3693-0896-7.ch001
• Milliken, J., Krause, K. (2002). State failure, state collapse, and state reconstruction: Concepts, lessons and strategies. Development and Change, 33(5), 753-774. https://doi.org/10.1111/1467-7660.t01-1-00247
• Mohammad, S., & Turney, P. (2013). Crowdsourcing a word-emotion association lexicon. Computational Intelligence, 29(3), 436–465. https://doi.org/10.48550/arXiv.1308.6297
• Nazlı, R. S., & Soylu, B. (2023). Doğal afet haberlerinin medyada sunumu: 6 Şubat 2023 Kahramanmaraş depremleri örneği. Uşak Üniversitesi Sosyal Bilimler Dergisi, 16(2), 44-57. https://dergipark.org.tr/tr/pub/usaksosbil/issue/82158/1412331#article_cite
• Naldi, M. (2019). A review of sentiment computation methods with R packages. ArXiv, abs/1901.08319. https://doi.org/10.48550/arXiv.1901.08319
• Özdemir, E. K. (2024). Social media in crisis communication: A case analysis of the 2023 Kahramanmaraş earthquakes. Akdeniz Üniversitesi İletişim Fakültesi Dergisi, 44, 112-131.
• Öze, N. (2024). 2023 Kahramanmaraş merkezli depremlerde enkaz altında kalan Kıbrıs Türk voleybol takımı haberlerinde doğruluk sorunu: Enformasyon, misenformasyon, dezenformasyon. Akademik Yaklaşımlar Dergisi, 15(1-Deprem Özel Sayısı-), 515-543. https://doi.org/10.54688/ayd.1385620
• Pang, B., & Lee, L. (2008). Opinion mining and sentiment analysis. Foundations and Trends® in Information Retrieval, 2(1–2), 1–135. https://doi.org/10.1561/1500000011
• Pektaş, U., & Davut, A. (2018). Uluslararası ilişkilerde kırılgan devlet söylemi: Nedenleri ve yaklaşımlar. Selçuk Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, (39), 1-14. https://dergipark.org.tr/tr/pub/susbed/issue/61821/924949
• Pignone, M., Amato, A., Nostro, C., Casarotti, E., Meletti, C., Quintiliani, M., & Lauciani, V. (2022). Public earthquake communication in Italy through a multi-source social media platform: The INGVterremoti experience (2010–2022). Frontiers in Earth Science, 10, 1003867. https://doi.org/10.3389/feart.2022.1003867
• Polyakova, O., & Kuzina, M. (2024). Depicting sustainability awareness in Turkey-Syria earthquake news coverage via sentiment analysis. In text mining and sentiment analysis in climate change and environmental sustainability (pp. 39-60). IGI Global. https://doi.org/10.4018/979-8-3693-7230-2.ch003
• Pozzi, F. A., Fersini, E., Messina, E., & Liu, B. (2017). Challenges of sentiment analysis in social networks: An overview. In Sentiment Analysis in Social Networks (pp. 1–11). Elsevier. https://doi.org/10.1016/B978-0-12-804412-4.00001-2
• Puschmann, C., & Powell, A. (2018). Turning words into consumer preferences: How sentiment analysis is framed in research and the news media. Social Media+ Society, 4(3), 205. https://doi.org/10.1177/2056305118797724
• R Core Team. (2023). R: A language and environment for statistical computing [Computer software]. R Foundation for Statistical Computing. https://www.R-project.org/
• Rostami, R., Tavakoli, F., & Forouzesh, R. (2022). Challenges of rapid relief in Sisakht earthquake crisis management in Kohgiluyeh and Boyer-Ahmad province, Iran: A review Study. Sci J Rescue Relief, 14(1), 1-10. https://doi.org/10.1016/j.ijdrr.2022.103512
• Rozado, D., Hughes, R., & Halberstadt, J. (2022). Longitudinal analysis of sentiment and emotion in news media headlines using automated labelling with Transformer language models. PLOS ONE, 17(10), e0276367. https://doi.org/10.1371/journal.pone.0276367
• Sağıroğlu, A. Z., Ünsal, R., Özenci, F. (2023). Deprem sonrası göç ve insan hareketlilikleri durum değerlendirme raporu. AYBÜ-GPM Rapor Serisi-15. Ankara: Ankara Yıldırım Beyazıt Üniversitesi Göç Politikaları Uygulama ve Araştırma Merkezi (AYBÜ-GPM).
• Şahin, D., & Demirbilek, E. Z. (2023). Doğal afet ve kriz yönetiminde sosyal medyanın etkisi: Kahramanmaraş merkezli deprem felaketi üzerine bir inceleme. Selçuk Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 51, 322-333. https://doi.org/10.52642/susbed.1289335
• Salik-Ata, N. (2023). Kahramanmaraş merkezli 6 Şubat depremlerinin kriz yönetimi bağlamında değerlendirilmesi. Meriç Uluslararası Sosyal ve Stratejik Araştırmalar Dergisi, 7(Özel Sayı), 59-77. https://doi.org/10.54707/meric.1327520
• Serin, E., & Ünlü, S. (2024). Sosyal medya çağının salgını bilgi dezenformasyonu: Twitter üzerinden 6 Şubat Kahramanmaraş depremi hakkında bir değerlendirme. İletişim ve Toplum Araştırmaları Dergisi, 4(1), 1-16. https://doi.org/10.59534/jcss.1333439
• Shahbazi, M., Ehnis, C., Shahbazi, M., & Bunker, D. (2018). Tweeting from the shadows: Social media convergence behaviour during the 2017 Iran-Iraq earthquake. Proceedings of ISCRAM Asia Pacific.
• Sheikh, D. A. R., Khan, S., & Sultan, D. A. (2024). Despair, hope, and politics: A semiotic analysis of online media cartoons on the Turkey and Syria earthquake 2023. Migration Letters, 21(S9), 297–310. https://doi.org/10.59670/ml.v21iS9.9798
• Silge, J., & Robinson, D. (2017). Text mining with R: A tidy approach. O’Reilly Media, Inc.
• Tarakcı, H. N. (2023). Afet iletişimi ve Twitter: Kahramanmaraş depremi özelinde bir içerik ve duygu analizi araştırması. Gümüşhane Üniversitesi İletişim Fakültesi Elektronik Dergisi, 11(2), 1816-1850. https://doi.org/10.19145/e-gifder.1353553
• Thelwall, M. (2017). Sentiment Analysis. In L. Sloan & A. Quan-Haase (Eds.), The SAGE handbook of social media research methods. Sage.
• UNFPA. (2023). Türkiye-Syria earthquake joint situation report #2. https://turkiye.unfpa.org/en/earthquake-joint-SitRep-2
• Usta, E., & Yükseler, M. (2021). Afetlerde sosyal medya kullanımı ve etik ikilemler: İzmir Seferihisar Depremi örneği. Afet ve Risk Dergisi, 4(2), 249-269. https://doi.org/10.35341/afet.981246
• Uzun, C. (2023). 6 Şubat depremi ve Twitter duygu analizi. Türk Dili ve Edebiyatı Dergisi, 63(2), 503-517. https://doi.org/10.26650/TUDED2023-1350807
• Welbers, K., Van Atteveldt, W., & Benoit, K. (2017). Text analysis in R. Communication Methods and Measures, 11(4), 245–265. https://doi.org/10.1080/19312458.2017.1387238
• Wiedemann, G. (2016). Text mining for qualitative data analysis in the social sciences. Springer Berlin Heidelberg.
• Wu, B., & Shen, H. (2015). Analyzing and predicting news popularity on Twitter. International Journal of Information Management, 35(6), 702–711. https://doi.org/10.1016/j.ijinfomgt.2015.07.003
• Xu, D., Zhuang, L., Deng, X., Qing, C., & Yong, Z. (2020). Media exposure, disaster experience, and risk perception of rural households in earthquake-stricken areas: Evidence from rural China. International journal of environmental research and public health, 17(9), 3246. https://doi.org/10.3390/ijerph17093246
• Yalçın, E. (2023). Doğal afetlerin doğal olmayan sonuçları: Gazetelerin deprem haberciliği. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi, (78), 188-210. https://doi.org/10.51290/dpusbe.1336124
• Yurdigül, Y., Bayraktar, R., & Çil, S. (2024). A study on Kahramanmaraş Earthquake survivors: “Social media platforms were more effectively used than the traditional media”. Connectist: Istanbul University Journal of Communication Sciences, 0(66), 211-229. https://doi.org/10.26650/CONNECTIST2024-1460282
• Zanoletti, A., & Bontempi, E. (2024). The impacts of earthquakes on air pollution and strategies for mitigation: A case study of Turkey. Environmental Science and Pollution Research, 31(16), 24662-24672. https://doi.org/10.1007/s11356-024-32592-8
• Zhang, L., & Liu, B. (2017). Sentiment analysis and opinion mining. In C. Sammut & G. I. Webb (Eds.), Encyclopedia of machine learning and data mining (pp. 1152–1161). Springer US. https://doi.org/10.1007/978-1-4899-7687-1_907