Turkiye Klinikleri Journal of Biostatistics

.: ORIGINAL RESEARCH
COVID-19 Pandemisi ile İlgili Twitter Mesajlarının Metin Madenciliği Tekniği İle Değerlendirilmesi
Evaluation of Twitter Messages Related to COVID-19 Pandemic Using Text Mining Technique
Ebru TEMİZHANa, Mehmet MENDEŞa
aÇanakkale Onsekiz Mart Üniversitesi Ziraat Fakültesi, Zootekni Bölümü Biyometri ve Genetik ABD, Çanakkale, TÜRKİYE
Turkiye Klinikleri J Biostat. 2021;13(2):185-200
doi: 10.5336/biostatic.2020-79992
Article Language: TR
Full Text
ÖZET
Amaç: Bu çalışma, yeni tip korona virüs hastalığı-2019 [coronavirus disease-2019 (COVID-19)] ile ilgili sosyal medyada yapılan paylaşımların ve atılan mesajların metin madenciliği tekniği (text mining technique) ile değerlendirilerek halkın bu salgına bakış açısını ve düşünceleri hakkında özetleyici bilgi üretmek amacıyla yürütülmüştür. Gereç ve Yöntemler: Bu amaçla, COVID-19 salgını ile ilgili atılan 40.000 Twitter mesajı metin madenciliği tekniği ile değerlendirilmiştir. Bulgular: Yapılan metin madenciliği analizi sonucunda, çalışmaya dâhil edilen Twitter kullanıcılarının tweetlerinde esas itibarıyla maske, COVID-19, Ankara Wuhan ve Bilim Kurulu olmak üzere 4 kelime üzerinde odaklandıkları ve yaptıkları paylaşımların bu 4 kelime etrafında şekillendiği belirlenmiştir. Aynı zamanda dikkate alınan Twitter kullanıcılarının, gündemlerini meşgul eden bu 4 kelimeye ilişkin duygu analizleri de (sentiment analysis) yapılmıştır. Bu vesile ile bireylerin gündemlerinde önemli bir yer teşkil eden maske, COVID-19, Ankara Wuhan ve Bilim Kurulu kelimelerinin duygularını nasıl etkilediklerine ilişkin bilgi üretilmesi de mümkün olmuştur. Yapılan duygu analizi sonucunda, bireylerin özellikle COVID-19 kelimesini duymaları ya da bundan bahsedilmesinin kendilerinde negatif bir duygu oluşturdukları sonucuna varılmıştır. Aynı zamanda Bilim Kurulunun kararlarının halkın üzerinde dikkate değer bir etki bıraktığı görülmüştür. Sonuç: Metin madenciliği ve duygu analizleri sonuçları birlikte değerlendirildiğinde halkın COVID-19 salgınının, halkın gündemini ciddi bir şekilde meşgul ettiği ve duyduklarında en fazla etkilendikleri terimlerin maske, COVID-19, Ankara Wuhan ve Bilim Kurulu olduğu sonucuna varılmıştır.

Anahtar Kelimeler: COVID-19; metin madenciliği; duygu analizi; regresyon analizi; maske
ABSTRACT
Objective: This study has been carried out to generate summarized information about the public's perspective and thoughts on coronavirus disease-2019 (COVID-19) pandemic by evaluating the posts and messages sent on social media about COVID-19 pandemic with the text mining technique. Material and Methods: For this purpose, 40.000 Twitter messages have sent regarding the COVID-19 outbreak were evaluated with the text mining technique. Results: As a result of the text mining analysis, it was determined that the tweets of the Twitter users included in the study focused mainly on four words, mask, COVID-19, Ankara Wuhan and the scientific committee, and their posts were shaped around these four words. At the same time, sentiment analysis was also performed after text mining analysis for four words that occupy the agendas of twitter users. Thus, it was possible to produce information about how the words mask, COVID-19, Ankara Wuhan and scientific committee, which constitute an important place in the agenda of Twitter users, affect their emotions. As a result of the sentiment analysis, it was concluded that individuals especially hearing the word COVID-19 or mentioning this word led to have a negative emotion in themselves. It was also observed that the decisions of the science committee have left a remarkable impact on the people. Conclusion: When the results of text mining and sentiment analysis were evaluated together, it was concluded that the people's agenda were seriously occupied by the COVID-19 pandemic. It was concluded that the terms that people were most affected by when they hear are mask, COVID-19, Ankara Wuhan and the scientific committee.

Keywords: COVID-19; text mining; sentiment analysis; regression analysis; mask
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