Global impact of the pandemic on education: a study of natural language processing


Ayaz T. B., Uslu M. S., Agcabay I., Ahmad F., Korkmaz O. F., Kureksiz M., ...Daha Fazla

2022 Innovations in Intelligent Systems and Applications Conference, ASYU 2022, Antalya, Türkiye, 7 - 09 Eylül 2022 identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/asyu56188.2022.9925311
  • Basıldığı Şehir: Antalya
  • Basıldığı Ülke: Türkiye
  • Anahtar Kelimeler: COVID-19, Deep Learning, Education, LSTM, Sentiment Analysis, Social Media
  • İstanbul Kültür Üniversitesi Adresli: Evet

Özet

School closures due to the Covid-19 pandemic have changed education forever and we have witnessed the rise of online learning platforms. The education units of the countries made great efforts to adapt to this new order. The expanding, quick spread of the virus and careful steps have prompted the quest for reasonable choices for continuing education to guarantee students get appropriate education and are not impacted logically or mentally. Different methods were attempted to understand how students were affected by this big change. In addition to the significance of traditional surveys and consulting services, the utilization of social media analysis is used as a supportive approach. This paper analyzes the feedback of students on social media via tweets. Deep sentiment analysis is employed to identify embedded emotions such as negative, neutral, and positive. We also aimed to classify irrelevant tweets as the fourth category. Our experiments showed that the tweets are mostly biased toward negative emotions.