Cross-Cultural Differences in Public Discourse on COVID-19 Vaccination in the United States and South Korea: Cross-Sectional Analysis Using Natural Language Processing

Public perceptions of COVID-19 vaccines and related information needs differ between the 2 countries, shaped by cultural context, trust in government, and information-seeking environments. Analysis of social question and answer data from the 2 countries reveals shared information needs but divergent sentiment patterns. These findings highlight the value of social media data for public health research and the need for culturally and platform-specific communication strategies.

Authors

Institutions

Publication Details

Journal
JMIR Formative Research
Published
2026-03-05
DOI
https://doi.org/10.2196/84791
Primary Topic
Computational and Text Analysis Methods
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Cross-Cultural Differences in Public Discourse on COVID-19 Vaccination in the United States and South Korea: Cross-Sectional Analysis Using Natural Language Processing

Sou Hyun Jang, Yong Jeong Yi, Haewoon Kwak, Sangpil Youm
JMIR Formative Research
Computational and Text Analysis Methods
article

Cross-Cultural Differences in Public Discourse on COVID-19 Vaccination in the United States and South Korea: Cross-Sectional Analysis Using Natural Language Processing

Sou Hyun Jang, Yong Jeong Yi, Haewoon Kwak, Sangpil Youm
article en

Abstract

Public perceptions of COVID-19 vaccines and related information needs differ between the 2 countries, shaped by cultural context, trust in government, and information-seeking environments. Analysis of social question and answer data from the 2 countries reveals shared information needs but divergent sentiment patterns. These findings highlight the value of social media data for public health research and the need for culturally and platform-specific communication strategies.

JMIR Formative ResearchVol. 10
Korea University (KR), University of Florida (US), Indiana University Bloomington (US), Naver (South Korea) (KR), Sungkyunkwan University (KR)
Good health and well-being
Openalex Percentile: Top 53%
Computational and Text Analysis Methods
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.