Public Opinions about Online Learning during COVID-19: A Sentiment Analysis Approach

被引：36

作者：

Bhagat, Kaushal Kumar ^{[1
]}

Mishra, Sanjaya ^{[2
]}

Dixit, Alakh ^{[3
]}

Chang, Chun-Yen ^{[4
]}

机构：

[1] Indian Inst Technol Kharagpur, Ctr Educ Technol, Kharagpur 721302, W Bengal, India

[2] Commonwealth Learning, Burnaby, BC V5H 4M2, Canada

[3] Indian Inst Technol Kharagpur, Dept Min Engn, Kharagpur 721302, W Bengal, India

[4] Natl Taiwan Normal Univ, Grad Inst Sci Educ, Taipei 116, Taiwan

来源：

SUSTAINABILITY | 2021年 / 13卷 / 06期

关键词：

COVID-19; pandemic; online learning; sentiment analysis; web scraping; PEOPLE;

D O I：

10.3390/su13063346

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

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.

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页数：12

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