Sosyal Medyada Duygu Analizi: COVID-19 Sürecinde 5G Algısı

Öz

Bu çalışmada toplum için fırsatlar yaratacak yeni yetenekler getirmesi beklenen beşinci nesil hücresel ağlar (5G) ile COVID-19 aşısının dünya genelinde insanlar üzerinde oluşturduğu algının Duygu Analizi yöntemi ile ölçülmesi hedeflenmektedir. Bu amaçla, yaygın olarak kullanılan bir sosyal medya aracı olan Twitter’dan Ekim – Aralık 2020 tarihleri arasında 25642 adet tweet çekilmiş ve Python yazılımı aracılığı ile hesaplamalar yapılmıştır. Buna göre dünya genelinde Twitter üzerinden fikrini beyan eden kişilerin %36,4’ünün 5G ile COVID-19 aşısı hakkında pozitif algıya sahip olduğu görülmüştür. Tweet atan kişilerin %35,6’sının ise konuyla ilgili olarak pozitif ya da negatif görüşe sahip olmadığı ve %28’inin de negatif görüş bildirdiği sonucuna varılmıştır. Tüm tweetler için genel duygu skoru ortalaması 0,15 olarak bulunmuştur. Çalışmada ayrıca verilere makine öğrenmesi yöntemlerinden Sınıflandırma ve Regresyon Ağaçları (CART), Naïve Bayes (NB), k-En Yakın Komşuluk (KNN) ve Rastgele Orman (RF) algoritmaları uygulanmıştır. Elde edilen bulgulara göre sınıflandırmada en iyi sonuçları 0,7852 kesinlik (P) ve 0,7445 doğruluk (A) değerleri ile NB; 0,8209 duyarlılık (R) değeri ile KNN ve 0,7866 F-ölçütü (F) değeri ile RF algoritmaları vermiştir.

Anahtar Kelimeler

• 5G
• COVID-19
• Duygu Analizi
• Makine Öğrenmesi
• Sınıflandırma Algoritmaları

Sentiment Analysis on Social Media: The 5G Perception During COVID-19 Process

Öz

This study is aimed at measuring the perception created by the COVID-19 vaccines on people around the world using Sentiment Analysis – taking into account the fifth generation (5G) cellular networks, which are expected to bring new capabilities that will create opportunities for society. For this purpose, 25642 tweets were taken from Twitter between October and December 2020 and analyzed using Python software. Accordingly, 36.4% of people worldwide who expressed their opinions on Twitter have a positive perception of 5G and the COVID-19 vaccine, also 35.6% of the tweeters do not have a positive or negative view (neutral) has been observed. However, it was observed that 28% of the people expressed negative opinions. The overall sentiment score is 0.15. Also, in this study, Classification and Regression Trees (CART), Naïve Bayes (NB), k-Nearest Neighbour (KNN), and Random Forest (RF) algorithms were applied. According to the findings, the best results were obtained by NB with 0,7852 precision (P) and 0,7445 accuracy (A) values, KNN with 0,8209 recall (R) value, and RF with 0,7866 F-measure (F) value.

Anahtar Kelimeler

• 5G
• COVID-19
• Sentiment Analysis
• Machine Learning
• Classification Algorithms

Kaynakça

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