Jain, G, Wamba, SF and Shrivastava, A (2022) Public Sentiments towards the COVID-19 Pandemic: Insights from the Academic Literature Review and Twitter Analytics. International Journal of Stress Management. ISSN 1072-5245 (In Press)

[thumbnail of Paper - COVID 160222.pdf] Text
Paper - COVID 160222.pdf - Accepted Version
Restricted to Repository staff only
Available under License Creative Commons Attribution Non-commercial.

Download (1MB)


The recent COVID-19 pandemic has severely impacted nations across the globe. Not only has it created economic shocks, but also long-term impacts on the social and psychological behaviors of the public. This can be attributed to the severity of the pandemic and because of the preventive and control measures such as global lockdowns, social distancing, and selfisolation that the governments imposed. Previous studies have reported significant changes in human emotions and behaviors are used to measure public sentiments about certain phenomena (such as the recent pandemic). The present study aims to study the public's sentiments during the COVID-19 outbreak based on an analytics review of public tweets highlighting changes in emotions. A dataset of 58,320 tweets extracted from Twitter and 61 academic articles was explored to analyze behavioral and emotional changes during previous and current pandemic situations. We chose the RPA – COV (Research Process Approach – COVID-19) approach, which was combined with the LBTA (Literature-Based Thematic Analysis) and the COVTA (COVID-19 Twitter Analytics). The sentiments' analysis results were coupled with word-tree analysis and highlighted that the public showed more highly neutral, positive, and mixed emotions than negative ones. The analysis pointed that people may react differently on Twitter as compared to real-life circumstances. The present study makes a significant contribution towards understanding how the public express their sentiments in pandemic situations.

Item Type: Article
Additional Information: The final version of this accepted manuscript will be available directly from the publisher on publication.
Uncontrolled Keywords: Sentiment analysis; pandemic; COVID-19; Twitter analytics; Thematic analysis
Subjects: H Social Sciences > H Social Sciences (General)
Divisions: Faculty of Humanities and Social Sciences > Keele Business School
Depositing User: Symplectic
Date Deposited: 28 Mar 2022 08:20
Last Modified: 28 Mar 2022 08:20
URI: https://eprints.keele.ac.uk/id/eprint/10781

Actions (login required)

View Item
View Item