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

Publication date: Jun 24, 2025

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 public collectively interprets risk and create group identities, informing public health strategies. This 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. We 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. This 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. 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.

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Concepts Keywords
Experts comment
Future Communication
Lockdownskepticism computational grounded theory
Online computational methods
conceptualizations
coronavirus
COVID-19
COVID-19
Grounded Theory
grounded theory
Humans
Internet
online communities
pandemic
Pandemics
qualitative
risk perception
SARS-CoV-2
SARS-CoV-2
thematic analysis
topic modeling
word embeddings

Semantics

Type Source Name
disease MESH COVID-19
disease IDO role
disease IDO process
drug DRUGBANK Ranitidine
disease MESH infection
disease MESH heart attack
disease MESH death
disease MESH paranoia
disease MESH panic
disease IDO host
disease MESH drug addiction
drug DRUGBANK Tropicamide
disease MESH uncertainty
disease MESH anxiety
disease MESH depression
drug DRUGBANK Oxygen
disease IDO intervention
disease IDO susceptibility
disease MESH noncommunicable diseases
disease MESH tourette syndrome
disease MESH tic disorders
drug DRUGBANK Amlodipine
disease MESH Emergencies
drug DRUGBANK Coenzyme M
drug DRUGBANK Hydrocortisone
disease IDO replication
pathway REACTOME Reproduction

Original Article

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