Big data analysis of Terror Management Theory's predictions in the COVID-19 pandemic

Chew H.K., Peter (2022) Big data analysis of Terror Management Theory's predictions in the COVID-19 pandemic. Omega: Journal of Death and Dying. (In Press)

[img] PDF (Publisher Accepted Version) - Published Version
Restricted to Repository staff only

DOI: 10.1177%2F00302228221092583
View at Publisher Website: https://doi.org/10.1177%2F00302228221092...
 
1


Abstract

The current study aimed to address the limitations of the terror management theory literature by using big data analysis to examine the theory’s predictions in the COVID-19 pandemic. Specifically, Google Trends were examined before and after the first COVID-19 case was identified in Singapore. The results showed that there was a significant increase in mortality salience, intergroup conflict, and prosocial behavior, and a significant decrease in materialism after the first COVID-19 case was identified. However, no significant differences were found for anxiety. Limitations include the assumption that search terms reflect intentions that would eventually lead to a relevant behavior and the lack of data from other sources to corroborate with the results from Google Trends. Future research could use data from other sources to examine the effects of COVID-19 on theoretically relevant behaviors.

Item ID: 73597
Item Type: Article (Research - C1)
ISSN: 1541-3764
Keywords: terror management theory, mortality salience, big data analysis, Google Trends, COVID-19
Copyright Information: © The Author(s) 2022
Date Deposited: 01 Jun 2022 03:51
FoR Codes: 52 PSYCHOLOGY > 5205 Social and personality psychology > 520505 Social psychology @ 100%
SEO Codes: 28 EXPANDING KNOWLEDGE > 2801 Expanding knowledge > 280121 Expanding knowledge in psychology @ 100%
Downloads: Total: 1
More Statistics

Actions (Repository Staff Only)

Item Control Page Item Control Page