Mackey, T., Purushothaman, V., Li, J., Shah, N., Nali, M., Bardier, C. et al. (2020). Machine Learning to Detect Self-Reporting of Symptoms, Testing Access, and Recovery Associated with COVID-19 on Twitter: Retrospective Big Data Infoveillance Study. JMIR Public Health and Surveillance, 6, Article ID: e19509.
https://doi.org/10.2196/19509

has been cited by the following article:

• TITLE: How People Show Their Emotions towards COVID-19 on Twitter Platform

  AUTHORS: Lu Zhao

  KEYWORDS: Social Media, COVID-19, Sentiment Analysis

  JOURNAL NAME: Advances in Journalism and Communication, Vol.10 No.2, June 7, 2022

  ABSTRACT: The pandemic that has lasted for more than three years exerted a significant influence on the life of people, especially on their physical and mental health of people. The study intends to find out how people express their sentiments on social media platforms—Twitter. It will adopt the quantitative methodology in analyzing the data. The secondary data will be collected from the Web page via the Chrome extension with WDRA software. By means of making the analysis, the study shows that there was a great change before and after the pandemic.