Public opinions about online learning during covid-19: A sentiment analysis approach

Kaushal Kumar Bhagat, Sanjaya Mishra, Alakh Dixit, Chun Yen Chang*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

42 Citations (Scopus)


The aim of this study was to analyze public opinion about online learning during the COVID-19 (Coronavirus Disease 2019) pandemic. A total of 154 articles from online news and blogging websites related to online learning were extracted from Google and DuckDuckGo. The articles were extracted for 45 days, starting from the day the World Health Organization (WHO) declared COVID-19 a worldwide pandemic, 11 March 2020. For this research, we applied the dictionary-based approach of the lexicon-based method to perform sentiment analysis on the articles extracted through web scraping. We calculated the polarity and subjectivity scores of the extracted article using the TextBlob library. The results showed that over 90% of the articles are positive, and the remaining were mildly negative. In general, the blogs were more positive than the newspaper articles; however, the blogs were more opinionated compared to the news articles.

Original languageEnglish
Article number3346
JournalSustainability (Switzerland)
Issue number6
Publication statusPublished - 2021 Mar 2


  • COVID-19 pandemic
  • Online learning
  • Sentiment analysis
  • Web scraping

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Environmental Science (miscellaneous)
  • Geography, Planning and Development
  • Energy Engineering and Power Technology
  • Hardware and Architecture
  • Management, Monitoring, Policy and Law
  • Computer Networks and Communications
  • Renewable Energy, Sustainability and the Environment


Dive into the research topics of 'Public opinions about online learning during covid-19: A sentiment analysis approach'. Together they form a unique fingerprint.

Cite this