Navigating in Turbulent Times: Using Social Media to Examine Small and family-Owned Business Topics and Sentiments during the COVID-19 Crisis

Shaun Meric Menezes (), Ashok Kumar () and Shantanu Dutta ()
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Shaun Meric Menezes: University of Ottawa
Ashok Kumar: University of Ottawa
Shantanu Dutta: University of Ottawa

Information Systems Frontiers, 2025, vol. 27, issue 4, No 17, 1691 pages

Abstract: Abstract During a crisis, small and family-owned businesses tend to experience more severe economic consequences than their larger counterparts and often lack financial resources needed to weather the challenges brought about by the crisis. To comprehend the distinct challenges and concerns of small and family-owned businesses during a major crisis, this research study focuses on the recent COVID-19 pandemic, which had a catastrophic effect on businesses and societies alike. To that effect, we address two research questions: First, what topics pertaining to small and family-owned businesses do social media users discuss during the COVID-19 pandemic? To achieve this goal, we employ the BERTopic model, a state-of-the-art technique for topic modeling, to identify and categorize prevalent themes arising from the discourse. Second, what is the impact of major government announcements on these discussions? Specifically, we study how sentiments change around a major government announcement aimed at supporting small businesses in the face of the pandemic. Our findings suggest that government announcements do not change the negative sentiments for most of the topics. This highlights the ineffectiveness of government announcements in alleviating people’s concern related to small and family-owned business and underscores the importance of a better consultation process and communication strategy by policymakers. The implications of our study transcend recent COVID-19 effects, as World Health Organization (WHO) cautions that there could be even worse health and socio-economic crises in the future, and we need to be better prepared to handle subsequent devastating effects.

Keywords: Coronavirus; COVID-19; Topic model; BERTopic; Clustering; Social media (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s10796-024-10542-6

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