Covid-19 Salgını Esnasında VADER ile Twitter Duygu Analizi

Abstract

Avrupa'yı etkisi altına aldığından beri Covid-19 salgını, özellikle Amerika kıtasında hızla yayılmaya devam etmektedir. Güncel verilere bakıldığında virüs yaklaşık 250 milyon insanı etkilemiş ve beş milyondan fazla insanın ölümüne neden olmuştur. Özellikle Avrupa kıtasında salgının hızla yayılmasıyla birlikte bu konu sosyal medyada tartışılmaya başlanmıştır. Özellikle Twitter bu çalışma alanında en sık kullanılan mikroblogdur. Bu çalışmada, küresel COVID-19 salgını sırasında Twitter üzerinden birçok kişi, kuruluş ve devlet kurumu tarafından paylaşılan tweetlerin VADER Duygu Analizi yöntemi kullanılarak, duygu analizi gerçekleştirilmesi amaçlanmaktadır. Bu çalışmada #covid19, #Covid, #pandemic, #social-distance, #socialdistance, #covid-19, #corona-virius, #coronavirus, #Chinesevirus, #Chinese-virus hashtagleri kullanılmıştır. Bu hashtag'ler ile 1 Ocak 2020 ile 1 Temmuz 2020 tarihleri arasında Twitter'dan toplam 60.243.040 tweet toplanmıştır. Bu çalışmada, Covid-19 ile ilgili Twitter verilerinde ifade edilen duyguları sınıflandırmak için VADER kullanılmış ve ortaya çıkan tweetlerin bileşik puanları, çok olumlu, olumlu, nötr, olumsuz, çok olumsuz olmak üzere beş kategoriye ayrılmıştır. Ayrıca çalışmada, aylık olarak en sık toplanan metin verilerinin görselleştirilmesi için Wordcloud kullanılmış ve tweetlerin içeriğini daha iyi anlamak için tweetlere N-gram uygulanmıştır. Çalışmada elde edilen sonuçlar incelendiğinde, çıkışın farklı dönemlerinde Covid-19 ile ilgili paylaşılan tweetlerin farklı duygusal durumları yansıtması oldukça ilginçtir.

Keywords

• Covid-19
• Koronavirüs
• Duygu Analizi
• VADER
• Twitter

Twitter Sentiment Analysis During Covid-19 Outbreak with VADER

Abstract

The Covid-19 outbreak, which has been under the influence of Europe since then, continues to spread rapidly especially in the American continent. Looking at the current data, the virus has affected about 250 million people and has killed more than five million people. Especially with the rapid spread of the outbreak in the European continent, this issue started to be discussed in social media. In particular, Twitter is the most frequently used micro-blogging in this workspace. In this study, it is aimed to analyze the tweets shared by many people, organizations and government agencies through Twitter during the global COVID-19 outbreak with sentiment analysis using the VADER Sentiment Analysis method. The hashtags #covid19, #Covid, #pandemic, #social-distancing, #socialdistance, #covid-19, #corona-virius, #coronavirus, #Chinesevirus, #Chinese-virus were used in this study. With these hashtags, a total of 60,243,040 tweets were collected from Twitter between January 1, 2020 and July 1, 2020. In this study, we use the VADER to classify the sentiments expressed in Twitter data related to Covid-19 and the compound scores of the resulting tweets were divided into five categories: Highly Positive, Positive, Neutral, Negative, Highly Negative. In addition, in the study, the Wordcloud was used to visualize the most frequently collected text data monthly, and N-grams were applied to the tweets to better understand the content of the tweets. When the results obtained in the study are examined, it is quite interesting that the tweets shared about Covid-19 in different periods of the release reflect different sentimental situations.

Keywords

• Covid-19
• Coronavirus
• Sentiment Analysis
• VADER
• Twitter

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