Consumer communications and current events: a cross-cultural study of the change in consumer response to company social media posts due to the COVID-19 pandemic

Jia Li () and Rachel McCrary ()
Additional contact information
Jia Li: Wake Forest University

Journal of Marketing Analytics, 2022, vol. 10, issue 2, No 7, 173-183

Abstract: Abstract The COVID-19 pandemic has changed the lives of consumers in virtually every nation. Based upon the theory of psychological reactance and psychoevolutionary theory of emotion, we hypothesize how such lifestyle changes affect consumers perceiving and responding to companies' communications messages. The theories also suggest that consumers in different cultures may respond to COVID-19 differently. To test our hypotheses, we implemented a Python scraper to collect companies’ Instagram posts pre- and during the COVID-19 lockdown. A machine learning algorithm was applied on the collected post photos to automatically identify certain photo characteristics, such as indoor versus outdoor, and with a single person versus many people; a text mining and sentiment analysis was implemented on the collected post captions to identify the salient emotion each caption exhibited, such as joy and anticipation. After that, we conducted a regression discontinuity analysis of photo characteristics or caption emotion on number of likes or comments to identify consumers’ response change due to the COVID-19 pandemic. The estimation results supported our hypotheses and suggested tactics that could improve consumer communications effectiveness in this changed time. Viewing COVID-19 as an example of a current event in the ever-changing world, this paper suggests that such events could impact consumer response and behavior, and that companies’ marketing and advertising strategies should be responsive to such events.

Keywords: COVID-19; Consumer communications; Social media marketing; Cross-cultural study; Machine learning; Sentiment analysis; Regression discontinuity analysis (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://link.springer.com/10.1057/s41270-021-00138-3 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:pal:jmarka:v:10:y:2022:i:2:d:10.1057_s41270-021-00138-3

Ordering information: This journal article can be ordered from
http://www.springer. ... gement/journal/41270

DOI: 10.1057/s41270-021-00138-3

Access Statistics for this article

Journal of Marketing Analytics is currently edited by Maria Petrescu and Anjala Krishnen

More articles in Journal of Marketing Analytics from Palgrave Macmillan
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().