Exploring Conceptualizations of COVID-19 Risk in Ideologically Distinct Online Communities: A Computational Grounded Theory Analysis
BackgroundThe 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...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
JMIR Publications
2025-06-01
|
| Series: | Journal of Medical Internet Research |
| Online Access: | https://www.jmir.org/2025/1/e67968 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849684765190389760 |
|---|---|
| author | Tiwaladeoluwa B Adekunle Jeremy Foote Toluwani E Adekunle Nathan TeBlunthuis Laura K Nelson |
| author_facet | Tiwaladeoluwa B Adekunle Jeremy Foote Toluwani E Adekunle Nathan TeBlunthuis Laura K Nelson |
| author_sort | Tiwaladeoluwa B Adekunle |
| collection | DOAJ |
| description |
BackgroundThe 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 public collectively interprets risk and create group identities, informing public health strategies.
ObjectiveThis study aims to, first, explore how online communities with distinct ideologies create and reinforce divergent conceptualizations of risk and, second, identify the role of group identity in shaping the development and communication of risk interpretations in these communities.
MethodsWe used computational grounded theory, a multistep approach that includes pattern detection, hypothesis testing, and pattern confirmation to explore interpretations of risk and group identity in about 500,000 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 latent Dirichlet allocation topic modeling to identify 10 topics based on the frequency of term co-occurrence. In the hypothesis refinement step, we conducted a qualitative thematic analysis of 30 posts under each topic 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.
ResultsThis study found that Masks4All and LockdownSkepticism both centered risk in their conversations, but with divergent concerns related to the threat of COVID-19. While Masks4All emphasized the threat to health, LockdownSkepticism 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.
ConclusionsThis 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. |
| format | Article |
| id | doaj-art-8f9eaba9149a4f7fa1f9c661dc8fec3b |
| institution | DOAJ |
| issn | 1438-8871 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | JMIR Publications |
| record_format | Article |
| series | Journal of Medical Internet Research |
| spelling | doaj-art-8f9eaba9149a4f7fa1f9c661dc8fec3b2025-08-20T03:23:22ZengJMIR PublicationsJournal of Medical Internet Research1438-88712025-06-0127e6796810.2196/67968Exploring Conceptualizations of COVID-19 Risk in Ideologically Distinct Online Communities: A Computational Grounded Theory AnalysisTiwaladeoluwa B Adekunlehttps://orcid.org/0000-0003-2582-0948Jeremy Footehttps://orcid.org/0000-0002-0078-2925Toluwani E Adekunlehttps://orcid.org/0000-0002-2150-5177Nathan TeBlunthuishttps://orcid.org/0000-0002-3333-5013Laura K Nelsonhttps://orcid.org/0000-0001-8948-300X BackgroundThe 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 public collectively interprets risk and create group identities, informing public health strategies. ObjectiveThis study aims to, first, explore how online communities with distinct ideologies create and reinforce divergent conceptualizations of risk and, second, identify the role of group identity in shaping the development and communication of risk interpretations in these communities. MethodsWe used computational grounded theory, a multistep approach that includes pattern detection, hypothesis testing, and pattern confirmation to explore interpretations of risk and group identity in about 500,000 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 latent Dirichlet allocation topic modeling to identify 10 topics based on the frequency of term co-occurrence. In the hypothesis refinement step, we conducted a qualitative thematic analysis of 30 posts under each topic 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. ResultsThis study found that Masks4All and LockdownSkepticism both centered risk in their conversations, but with divergent concerns related to the threat of COVID-19. While Masks4All emphasized the threat to health, LockdownSkepticism 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. ConclusionsThis 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.https://www.jmir.org/2025/1/e67968 |
| spellingShingle | Tiwaladeoluwa B Adekunle Jeremy Foote Toluwani E Adekunle Nathan TeBlunthuis Laura K Nelson Exploring Conceptualizations of COVID-19 Risk in Ideologically Distinct Online Communities: A Computational Grounded Theory Analysis Journal of Medical Internet Research |
| title | Exploring Conceptualizations of COVID-19 Risk in Ideologically Distinct Online Communities: A Computational Grounded Theory Analysis |
| title_full | Exploring Conceptualizations of COVID-19 Risk in Ideologically Distinct Online Communities: A Computational Grounded Theory Analysis |
| title_fullStr | Exploring Conceptualizations of COVID-19 Risk in Ideologically Distinct Online Communities: A Computational Grounded Theory Analysis |
| title_full_unstemmed | Exploring Conceptualizations of COVID-19 Risk in Ideologically Distinct Online Communities: A Computational Grounded Theory Analysis |
| title_short | Exploring Conceptualizations of COVID-19 Risk in Ideologically Distinct Online Communities: A Computational Grounded Theory Analysis |
| title_sort | exploring conceptualizations of covid 19 risk in ideologically distinct online communities a computational grounded theory analysis |
| url | https://www.jmir.org/2025/1/e67968 |
| work_keys_str_mv | AT tiwaladeoluwabadekunle exploringconceptualizationsofcovid19riskinideologicallydistinctonlinecommunitiesacomputationalgroundedtheoryanalysis AT jeremyfoote exploringconceptualizationsofcovid19riskinideologicallydistinctonlinecommunitiesacomputationalgroundedtheoryanalysis AT toluwanieadekunle exploringconceptualizationsofcovid19riskinideologicallydistinctonlinecommunitiesacomputationalgroundedtheoryanalysis AT nathanteblunthuis exploringconceptualizationsofcovid19riskinideologicallydistinctonlinecommunitiesacomputationalgroundedtheoryanalysis AT lauraknelson exploringconceptualizationsofcovid19riskinideologicallydistinctonlinecommunitiesacomputationalgroundedtheoryanalysis |