Sakarya University Journal of Computer and Information Sciences

Yazarlar: Ahmet Anıl MÜNGEN, İ̇̇rfan AYGÜN, Mehmet KAYA

Konular:Bilgisayar Bilimleri, Yapay Zeka

DOI:10.35377/saucis.03.03.830867

Anahtar Kelimeler:COVID-19,LSTM,BERT,Sentiment Analysis,TF-IDF

Özet: Nowadays, social media and online sharing sites are frequently used to share thoughts about daily events. Thanks to the posts made by internet users on these platforms, first, quite big data is generated to interpret the agenda. More than 10,000 comments of more than 5000 users made about COVID-19 from online websites between 15 March and 15 May were collected in this study. Then, emotional analysis on these comments was carried out with BERT, GRU, LSTM and TF-IDF methods. The changes in the amount of user comments and the emotions reflected by the comments have been associated with the actual events of these dates. It has been determined which types of events affect users more. In addition, the emotional response changes of the users to the official COVID-19 statistics were measured and the peak points of the emotional changes were determined. Finally, the emotion classification methods applied were evaluated by user questionnaires and their successes were determined according to F-Measure.

---