Author :
Abstract
Bu çalışmada Türkiye tarafından geliştirilen Turkovac aşısı ile ilgili medyada yer alan haberler incelenmiştir. Araştırmanın kapsamını Hürriyet, Milliyet ve Posta gazetesinde yer alan 437 haber oluşturmuştur. Haberlerin elde edilmesinde web madenciliği teknikleri kullanılmıştır. Metin madenciliği yöntemleri kullanılarak haberlerin başlık, özet ve içerikler için nicel içerik analizi yapılmıştır. Duygu analizi sonuçlarına bakıldığında, başlık, özet ve içeriklerde daha çok olumlu yönde haberler yapıldığı tespit edilmiştir. Kelime bulutları incelendiğinde, en çok “aşı”, “Erdoğan”, “bakan”, “koca” ve “sağlık” gibi kelimelerin kullanıldığı görülmüştür. Başlık ve özet kapsamında kelimeler arasındaki ağ analizlerine bakıldığında ise, “aşı-Turkovac”, “yerli-aşı”, “Erdoğan-Cumhurbaşkanı”, “Bakan-Koca” ve “kurul-bilim” gibi kelimelerin daha çok birlikte kullanıldığı belirlenmiştir. Bireyleri yönlendirebilme noktasında medyanın olası etkisi dikkate alındığında, Turkovac aşısı ile ilgili genel olarak pozitif haberlerin yapılmasının aşılanma sürecini olumlu yönde etkileyebileceği söylenebilir.
Keywords
Abstract
In this study, the news in the media about the Turkovac vaccine developed by Turkey was examined. The scope of the research consisted of 437 news published in Hürriyet, Milliyet and Posta newspapers. Web mining techniques were used to obtain the news. Quantitative content analysis was made for the title, summary and contents of the news by using text mining methods. When the sentiment analysis results are examined, it has been determined that more positive news is made in the title, summary and contents. When the word clouds were examined, it was seen that the words such as "vaccine", "Erdogan", "minister", "koca" and "health" were mostly used. When looking at the network analysis between the words in the title and summary, it was determined that words such as "vaccine-Turkovac", "domestic-vaccine", "Erdogan-President", "Minister-Koca" and "board-science" were used together. Considering the possible impact of the media on directing individuals, it can be said that generally positive news about the Turkovac vaccine can positively affect the vaccination process.
Keywords
- Anadolu Ajansı. (2021a). “TURKOVAC Acil Kullanım Onayı Aldı”,
- Anadolu Ajansı. (2021a). “TURKOVAC Acil Kullanım Onayı Aldı”,(https://web.archive.org/web/20211222132108/https://www.aa.com.tr/tr/koronavirus/turkovac-acil-kullanim-onayi- aldi/2454541, Erişim tarihi: 27.12.2021).
- Anadolu Ajansı. (2021b). “Yerli Kovid-19 Aşısı TURKOVAC'ın Şehir Hastanelerinde Uygulanmasına Başlandı”, (https://www.aa.com.tr/tr/koronavirus/yerli-kovid-19-asisi-turkovacin-sehir-hastanelerinde-uygulanmasina-
- baslandi/2461044, Erişim tarihi: 30.12.2021).
- Akın, A. A. & Akın, M. D. (2007). “Zemberek, An Open Source Nlp Framework For Turkic Languages”, Structure, 10(1): 1-5.
- BBC. (2021). “Sağlık Bakanı Koca: Yerli Aşımız Turkovac Acil Kullanım Onayına Müracaat Edecek Aşamaya Geldi”, (https://www.bbc.com/turkce/haberler-turkiye-58506438, Erişim Tarihi: 02.09.2021).
- Benis, A.; Seidmann, A., & Ashkenazi, S. (2021). “Reasons for Taking The COVID-19 Vaccine by US Social Media Users”, Vaccines, 9(4): 315-320.
- Bos, W. & Tarnai, C. (1999). “Content Analysis in Empirical Social Research”, International Journal of Educational Research, 31(8): 659-671.
- Camprubí, R. & Coromina, L. (2016). “Content Analysis in Tourism Research”, Tourism Management Perspectives, 18: 134-140.
- Chaudhary, F. A.; Ahmad, B., Khalid, M. D., Fazal, A., Javaid, M. M. & Butt, D. Q. (2021). “Factors InfluencingCOVID-19 Vaccine Hesitancy and Acceptance Among the Pakistani Population”, Human Vaccines & Immunotherapeutics, 17(10): 3365-3370.
- Dal-Ré, R. (2021). “Placebo Control Group in COVID-19 Vaccine Trials: Context and Timing Matters”, European Journal of Clinical Pharmacology, 78: 523–526
- Dehkharghani, R.; Saygin, Y., Yanikoglu, B. & Oflazer, K. (2016). “Sentiturknet: A Turkish Polarity Lexicon for Sentiment Analysis”, Language Resources and Evaluation, 50(3): 667-685.
- Earnshaw, V. A.; Eaton, L. A., Kalichman, S. C., Brousseau, N. M., Hill, E. C. & Fox, A. B. (2020). “COVID-19Conspiracy Beliefs, Health Behaviors, And Policy Support”, Translational Behavioral Medicine, 10(4): 850-856.
- Esen, B. (2021). “COVID-19 Salgını Döneminde Aşı Milliyetçiliği ve Türkiye’nin Aşı Diplomasisi”, Ekonomi Politika ve Finans Araştırmaları Dergisi, 6(IERFM Özel Sayısı): 1-17.
- Foley, K.; McNaughton, D. & Ward, P. (2020). “Monitoring The ‘Diabetes Epidemic’: A Framing Analysis Of United Kingdom Print News 1993-2013”, PloS one, 15(1): 1-27.
- Forman, J. & Damschroder, L. (2007), "Qualitative Content Analysis", Jacoby, L. and Siminoff, L.A. (Ed.)Empirical Methods for Bioethics: A Primer (Advances in Bioethics, Vol. 11), Emerald Group Publishing Limited, Bingley.
- Hao, L. & Hao, L. (2008). “Automatic Identification of Stop Words in Chinese Text Classification”. International Conference on Computer Science and Software Engineering, 12-14 Dec. 2008, IEEE, Wuhan.
- Hellyer, N. E. & Haddock-Fraser, J. (2011). “Reporting Diet-Related Health Issues Through Newspapers: Portrayal of Cardiovascular Disease and Type 2 Diabetes”, Health Education Research, 26(1): 13-25.
- İşlek, E.; Özatkan, Y., Uslu, M. K. B., Arı, H. O., Çelik, H. & Yıldırım, H. H. (2021). “Türkiye’de COVID-19Pandemisi Yönetimi ve Sağlık Politikası Stratejileri”, Türkiye Sağlık Enstitüleri Başkanlığı Dergisi, 4(2): 54-65.
- Kaur, S. P. & Gupta, V. (2020). “COVID-19 Vaccine: A Comprehensive Status Report”, Virus Research, 288:1-12.Khalil, S. & Fakir, M. (2017). “R Crawler: An R Package for Parallel Web Crawling and Scraping”, Softwarex, 6: 98-106.
- Khanna, R. C.; Cicinelli, M. V., Gilbert, S. S., Honavar, S. G. & Murthy, G. V. (2020). “COVID-19 Pandemic: Lessons Learned and Future Directions”, Indian Journal of Ophthalmology, 68(5): 703-710.
- Kim, H. S. (2015). “Attracting Views and Going Viral: How Message Features and News-Sharing Channels Affect Health News Diffusion”, Journal of Communication, 65(3), 512-534
- Kim, J. H., Marks, F. & Clemens, J. D. (2021). “Looking Beyond COVID-19 Vaccine Phase 3 Trials”, Nature Medicine, 27(2): 205-211.
- Kumar, A.; Gupta, P. K. & Srivastava, A. (2020). “A Review of Modern Technologies for Tackling COVID-19 Pandemic”, Diabetes & Metabolic Syndrome: Clinical Research & Reviews, 14(4): 569-573.
- Li, Y.; Tenchov, R., Smoot, J., Liu, C., Watkins, S. & Zhou, Q. (2021). “A Comprehensive Review of the Global Efforts On COVID-19 Vaccine Development”, ACS Central Science, 7(4): 512-533.
- Lin, C. & He, Y. (2009). “Joint Sentiment/Topic Model for Sentiment Analysis”, In Proceedings of The 18th ACM Conference On Information and Knowledge Management, Hong Kong.
- Liu, B. & Zhang, L. (2012). “A Survey of Opinion Mining and Sentiment Analysis”, Springer, Boston, MA.
- Lone, S. A. & Ahmad, A. (2020). “COVID-19 Pandemic–An African Perspective”, Emerging Microbes & Infections, 9(1): 1300-1308.
- Lythgoe, M. P. & Middleton, P. (2020). “Ongoing Clinical Trials for The Management of The COVID-19 Pandemic”, Trends in Pharmacological Sciences, 41(6): 363-382.
- Medhat, W.; Hassan, A. & Korashy, H. (2014). “Sentiment Analysis Algorithms and Applications: A Survey”, Ain Shams Engineering Journal, 5(4): 1093-1113.
- Muehlethaler, C. & Albert, R. (2021). “Collecting Data On Textiles from The Internet Using Web Crawling and Web Scraping Tools”, Forensic Science International, 322: 1-21.
- Muric, G.; Wu, Y. & Ferrara, E. (2021). “COVID-19 Vaccine Hesitancy on Social Media: Building a PublicTwitter Data Set of Antivaccine Content, Vaccine Misinformation, and Conspiracies”, JMIR Public Health and Surveillance, 7(11):1-8.
- Okuhara, T.; Ishikawa, H., Okada, M., Kato, M. & Kiuchi, T. (2019). “Newspaper Coverage Before and After The HPV Vaccination Crisis Began in Japan: A Text Mining Analysis”. BMC Public Health, 19(1): 1-15.
- Ortigosa, A.; Martín, J. M. & Carro, R. M. (2014). “Sentiment Analysis in Facebook and Its Application to E- Learning”, Computers in Human Behavior, 31: 527-541.
- Pokhrel, S. & Chhetri, R. (2021). “A Literature Review on Impact of COVID-19 Pandemic on Teaching and Learning”, Higher Education for The Future, 8(1): 133-141.
- Sukanya, M. & Biruntha, S. (2012). “Techniques on Text Mining”, In 2012 IEEE International Conference onAdvanced Communication Control and Computing Technologies, 23-25 Aug. 2012, IEEE, Ramanathapuram, India.
- Viswanath, K.; Bekalu, M., Dhawan, D., Pinnamaneni, R., Lang, J. & McLoud, R. (2021). “Individual and Social Determinants of COVID-19 Vaccine Uptake”, BMC Public Health, 21(1): 1-10.
- Willis, D. E.; Andersen, J. A., Bryant‐Moore, K., Selig, J. P., Long, C. R., Felix, H. C., ... & McElfish, P. A.(2021). “COVID‐19 Vaccine Hesitancy: Race/Ethnicity, Trust, And Fear”, Clinical and Translational Science, 14(6): 2200-2207
