Social media and COVID‐19: Characterizing anti‐quarantine comments on Twitter. Issue 1 (22nd October 2020)

• Record Type: Journal Article
• Authors: Karami, Amir; Anderson, Mackenzie
• Is Part Of: Proceedings of the Association for Information Science and Technology. Volume 57:Issue 1(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-10-22
• Subjects: COVID‐19 -- quarantine -- social media -- twitter -- text mining; Information science -- Congresses; Information technology -- Congresses; Information science; Information technology; Conference papers and proceedings; 020
• DOI: 10.1002/pra2.349
• Languages: English
• ISSNs: 2373-9231

Abstract

Abstract: Social media has become a mainstream channel of communication during the COVID‐19 pandemic. While some studies have been developed on investigating public opinion on social media data regarding COVID‐19 pandemic, there is no study analyzing anti‐quarantine comments on social media. This study has collected and analyzed near 80, 000 tweets to understand anti‐quarantine social comments. Using text mining, we found 11 topics representing different issues such as comparing COVID‐19 and flu and health side effects of quarantine. We believe that this study shines a light on public opinion of people who are against quarantine.