Mapping the scholarly literature on the infodemic using topic modelling

Bibliographic Data

ID22206151
AuthorsGergely Ferenc Lendvai (0000-0003-3298-8087, Ludovika University of Public Service, corresponding author)
Year2026
Volume13
Pages102572
Publication date2026-06-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueSocial Sciences & Humanities Open (JOURNAL)
Journal identifiersISSN: 2590-2911 • E-ISSN: 2590-2911
PublisherElsevier BV (PUBLISHER)
DOI10.1016/j.ssaho.2026.102572
OpenAlexW7143695647
LanguageEN
References cited48

The present study aims to map the scholarly evolution of the infodemic as a research subject through a scientometric analysis of 852 peer-reviewed articles indexed in Web of Science between 2020 and 2024 building on scientometric methods and Structural Topic Modeling (STM). Findings reveal a sharp rise in publications during the pandemic years, peaking in 2022, followed by a remarkable decline in both output and citation impact. The STM uncovered 20 distinct topics, with dominant themes centred on health communication, misinformation, social media, and institutional trust. While several themes peaked early in the pandemic, others, such as institutional or public trust, gained prominence later. Topic correlations showed dense interlinkages but low modularity suggested conceptual fragmentation and weak field consolidation. The results highlight that infodemic scholarship remains an emergent, interdisciplinary domain, however, there is a need for stable theoretical foundations. • Infodemic research surged in 2020–2022, then sharply declined after 2022. • Citation impact peaked in 2020, followed by a steep, sustained drop. • STM reveals 20 topics dominated by health communication and misinformation. • Topic network shows dense interlinks but weak conceptual consolidation

Bibliometrics · Citation · Co-citation · Scholarship · Social media · Topic model · Computational and Text Analysis Methods · Data-Driven Disease Surveillance · Misinformation and Its Impacts

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