19th AIAI 2023, 14 - 17 June 2023, León, Spain

Sentiment analysis of tweets on online education during COVID-19

Elif Yıldırım, Harun Yazgan, Onur Özbek, Ahmet Can Günay, Büşra Kocaçınar, Öznur Şengel, Fatma Patlar Akbulut

Abstract:

  The global coronavirus disease (COVID-19) pandemic has devastated public health, education, and the economy worldwide. As of December 2022, more than 524 million individuals have been diagnosed with the new coronavirus, and nearly 6 million people have perished as a result of this deadly sickness, according to the World Health Organization. Universities, colleges, and schools are closed to prevent the coronavirus from spreading. Therefore, distance learning became a required method of advancing the educational system in contemporary society. Adjusting to the new educational system was challenging for both students and instructors, which resulted in a variety of complications. People began to spend more time at home; thus, social media usage rose globally throughout the epidemic. On social media channels such as Twitter, people discussed online schooling. Some individuals viewed online schooling as superior, while others viewed it as a failure. This study analyzes the attitudes of individuals toward distance education during the pandemic. Sentiment analysis was performed using natural language processing (NLP) and deep learning methods. Recurrent neural network (RNN) and one-dimensional convolutional neural network (1DCNN)-based network models were used during the experiments to classify neutral, positive, and negative contents.  

*** Title, author list and abstract as seen in the Camera-Ready version of the paper that was provided to Conference Committee. Small changes that may have occurred during processing by Springer may not appear in this window.