ArticleJournal of medical Internet research2020
The COVID-19 Infodemic: Infodemiology Study Analyzing Stigmatizing Search Terms.
Article in Journal of medical Internet research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
28 citing papers in PubMed, 1 synthesis or guideline pooled it, 66 citations in OpenAlex.
- Pooled it
- Evaluating Turkish society's approaches to hemorrhoid treatment using text mining and sentiment analysis methods.Frontiers in surgery · 2026Article
- Quality evaluation of stroke-related information on TikTok: a cross-sectional study.Scientific reports · 2025Article
- Review
- Intersecting Inequities in COVID-19 Vaccination: A Discourse Analysis of Information Use and Decision-Making Among Ethnically Diverse Parents in Canada.Journal of racial and ethnic health disparities · 2025Article
- Assessing Message Deployment During Public Health Emergencies Through Social Media: Empirical Test of Optimizing Content for Effective Dissemination.Journal of medical Internet research · 2024Article
- Understanding the "Infodemic" Threat: A Case Study of the COVID-19 Pandemic.Korean journal of family medicine · 2024Article
- The media risk of infodemic in public health emergencies: Consequences and mitigation approaches.PloS one · 2024Article
- COVID-19 infodemic and health-related quality of life in patients with chronic respiratory diseases: A multicentre, observational study.Journal of global health · 2023Observational
- COVID-19 activity risk calculator as a gamified public health intervention tool.Scientific reports · 2023Article
- Crowdsourcing Knowledge Production of COVID-19 Information on Japanese Wikipedia in the Face of Uncertainty: Empirical Analysis.Journal of medical Internet research · 2023Article
- Article
- A Clinical Psychological View about Delusional Characterizations in Subjects with Schizophrenia Spectrum Disorder during the COVID-19 Period.Journal of clinical medicine · 2023Review
- Exposing influence campaigns in the age of LLMs: a behavioral-based AI approach to detecting state-sponsored trolls.EPJ data science · 2023Article
- Human Mobility Restrictions and COVID-19 Infection Rates: Analysis of Mobility Data and Coronavirus Spread in Poland and Portugal.International journal of environmental research and public health · 2022Article
- The Impacts of Social Media Use and Online Racial Discrimination on Asian American Mental Health: Cross-sectional Survey in the United States During COVID-19.JMIR formative research · 2022Article
- COVID-19 preparedness and social dynamics in a Sub-Saharan Africa country, Benin.Health promotion international · 2022Article
- Types of Racism and Twitter Users' Responses Amid the COVID-19 Outbreak: Content Analysis.JMIR formative research · 2022Article
- An Analysis of the Deleterious Impact of the Infodemic during the COVID-19 Pandemic in Brazil: A Case Study Considering Possible Correlations with Socioeconomic Aspects of Brazilian Demography.International journal of environmental research and public health · 2022Article
- A new infodemiological approach through Google Trends: longitudinal analysis of COVID-19 scientific and infodemic names in Italy.BMC medical research methodology · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIn the context of the COVID-19 infodemic, the global profusion of monikers and hashtags for COVID-19 have found their way into daily communication and contributed to a backlash against China and the Chinese people.
objectiveThis study examines public engagement in crisis communication about COVID-19 during the early epidemic stage and the practical strategy of social mobilization to mitigate the infodemic.
methodsWe retrieved the unbiased values of the top-ranked search phrases between December 30, 2019, and July 15, 2020, which normalized the anonymized, categorized, and aggregated samples from Google Search data. This study illustrates the most-searched terms, including the official COVID-19 terms, the stigmatized terms, and other controls, to measure the collective behavioral propensities to stigmatized terms and to explore the global reaction to the COVID-19 epidemic in the real world. We calculated the ratio of the cumulative number of COVID-19 cases to the regional population as the cumulative rate (R) of a specific country or territory and calculated the Gini coefficient (G) to measure the collective heterogeneity of crowd behavior.
resultsPeople around the world are using stigmatizing terms on Google Search, and these terms were used earlier than the official names. Many stigmatized monikers against China (eg, "Wuhan pneumonia," G=0.73; "Wuhan coronavirus," G=0.60; "China pneumonia," G=0.59; "China coronavirus," G=0.52; "Chinese coronavirus," G=0.50) had high collective heterogeneity of crowd behavior between December 30, 2019, and July 15, 2020, while the official terms "COVID-19" (G=0.44) and "SARS-CoV-2" (G=0.42) have not become de facto standard usages. Moreover, the pattern of high consistent usage was observed in 13 territories with low cumulative rates (R) between January 16 and July 15, 2020, out of 58 countries and territories that have reported confirmed cases of COVID-19. In the scientific literature, multifarious naming practices may have provoked unintended negative impacts by stigmatizing Chinese people. The World Health Organization; the United Nations Educational, Scientific and Cultural Organization; and the media initiated campaigns for fighting back against the COVID-19 infodemic with the same mission but in diverse voices.
conclusionsInfodemiological analysis can articulate the collective propensities to stigmatized monikers across search behaviors, which may reflect the collective sentiment of backlash against China and Chinese people in the real world. The full-fledged official terms are expected to fight back against the resilience of negative perceptual bias amid the COVID-19 epidemic. Such official naming efforts against the infodemic should be met with a fair share of identification in scientific conventions and sociocultural paradigms. As an integral component of preparedness, appropriate nomenclatures should be duly assigned to the newly identified coronavirus, and social mobilization in a uniform voice is a priority for combating the next infodemic.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.