Application of Ensemble Techniques Based Sentiment Analysis to Assess the Adoption Rate of E-Learning During Covid-19 Among the Spectrum of Learners

Sirajudeen, S.; Balaganesh, Haleema Devi V. A.

The Corona Virus disease (COVID-19) epidemic outbreak leads to worldwide lockdown. Lockdown is enabled to be secure and to keep a correct social distance. According to the Government of India, every university, college and school has been closed defending against this threatening virus. This lockdown time presents an eye-opener for the digital services, for example, use of applications, generating virtual classrooms, online mock testing, online video quizzes, live lectures, deliberations, and document sharing and so on which provides more efficient than ever before. It mostly reveals essential e- learning in education, particularly during this isolation. This paper would assist in identifying attitudes of students’ towards e-learning during COVID-19 epidemics using Ensemble Learning-based Sentiment Analysis (ELSA) Algorithm. The study conducts for students studying in different schools, universities and colleges to obtain other data on e-learning involvement during these epidemics. Evaluation metrics, for example, precision, recall, F-score and accuracy are computed and examine for classification performance. © 2021, Springer Nature Switzerland AG.