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Accepted for/Published in: Journal of Medical Internet Research

Date Submitted: Oct 24, 2024
Date Accepted: Apr 6, 2025

The final, peer-reviewed published version of this preprint can be found here:

Exploring Conceptualizations of COVID-19 Risk in Ideologically Distinct Online Communities: A Computational Grounded Theory Analysis

Adekunle T, Foote J, Adekunle T, TeBlunthuis N, Nelson LK

Exploring Conceptualizations of COVID-19 Risk in Ideologically Distinct Online Communities: A Computational Grounded Theory Analysis

J Med Internet Res 2025;27:e67968

DOI: 10.2196/67968

PMID: 40553514

PMCID: 12238777

Co-creating Risk: Exploring Conceptualizations of COVID-19 Risk in Ideologically Distinct Online Communities

  • Tiwaladeoluwa Adekunle; 
  • Jeremy Foote; 
  • Toluwani Adekunle; 
  • Nate TeBlunthuis; 
  • Laura K Nelson

ABSTRACT

Background:

The COVID-19 pandemic has had a profound impact on societies and economies around the globe, and experts warn about the potential for similar crises in the future. Risk communication theories underscore that while the potential for harm is objective, risk perception is a subjective, socially derived interpretation. While there is broad literature on the social construction of risk, fewer studies examine the role of communities—online or offline—in developing and reinforcing distinct interpretations of the same risk event. During COVID-19, online communities emerged as individuals sought to make sense of the ongoing crisis. These communities offer an opportunity to gain important insights into how concerned publics collectively interpret risk and create group identities, informing public health strategies.

Objective:

This study aims to firstly, explore how online communities with distinct ideologies create and reinforce divergent conceptualizations of risk and secondly, identify the role of group identity in shaping the development and communication of risk interpretations in these communities.

Methods:

We used computational grounded theory, a multi-step approach that includes pattern detection, hypothesis testing, and pattern confirmation to explore interpretations of risk and group identity in ~70,000 comments from the subreddits r/LockdownSkepticism and r/Masks4All. In the pattern detection step of this study, we grouped comments by the post they were made on and then used LDA topic modeling to identify ten topics based on the frequency of term co-occurrence. In the hypothesis refinement step, we conducted a qualitative thematic analysis using Braun and Clarke’s approach. Finally, in the pattern confirmation step, we trained a Word2Vec word embedding model to validate emerging themes from the second step.

Results:

This study found that Masks4All(M4A) and LockdownSkepticism (LS) both centered risk in their conversations, but with divergent concerns related to the threat of COVID-19. While M4A emphasized the threat to health, LS questioned the necessity of preventive measures and focused on other risks: the threat to the economy, educational disruptions, and social isolation. Group identity was also found to shape collective meanings around risk, as community members in both subreddits affirmed group positions and condemned the outgroup.

Conclusions:

This study demonstrated that while both communities were concerned about COVID-19, their perceptions of risk focused on different aspects of the same risk event. This underscores the need for targeted interventions that engage with divergent ideologies and value systems across groups of people.


 Citation

Please cite as:

Adekunle T, Foote J, Adekunle T, TeBlunthuis N, Nelson LK

Exploring Conceptualizations of COVID-19 Risk in Ideologically Distinct Online Communities: A Computational Grounded Theory Analysis

J Med Internet Res 2025;27:e67968

DOI: 10.2196/67968

PMID: 40553514

PMCID: 12238777

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