| 1.
A Public Health Research Agenda for Managing Infodemics: Methods and Results of the First WHO Infodemiology Conference
JMIR Infodemiology 2021;1(1):e30979
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| 1496 | 271 | 116 | |
| 2.
TikTok as a Source of Health Information and Misinformation for Young Women in the United States: Survey Study
JMIR Infodemiology 2024;4(1):e54663
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| 7223 | 6 | 97 | |
| 3.
Monitoring Depression Trends on Twitter During the COVID-19 Pandemic: Observational Study
JMIR Infodemiology 2021;1(1):e26769
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| 799 | 17 | 80 | |
| 4.
Infodemic Signal Detection During the COVID-19 Pandemic: Development of a Methodology for Identifying Potential Information Voids in Online Conversations
JMIR Infodemiology 2021;1(1):e30971
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| 879 | 116 | 63 | |
| 5.
Analyzing Social Media to Explore the Attitudes and Behaviors Following the Announcement of Successful COVID-19 Vaccine Trials: Infodemiology Study
JMIR Infodemiology 2021;1(1):e28800
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| 394 | 163 | 48 | |
| 6.
Measuring the Burden of Infodemics: Summary of the Methods and Results of the Fifth WHO Infodemic Management Conference
JMIR Infodemiology 2023;3(1):e44207
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| 1445 | 153 | 39 | |
| 7.
Desensitization to Fear-Inducing COVID-19 Health News on Twitter: Observational Study
JMIR Infodemiology 2021;1(1):e26876
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| 771 | 76 | 37 | |
| 8.
The Role of Social Media in Health Misinformation and Disinformation During the COVID-19 Pandemic: Bibliometric Analysis
JMIR Infodemiology 2023;3(1):e48620
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| 2068 | 7 | 37 | |
| 9.
Public Opinion and Sentiment Before and at the Beginning of COVID-19 Vaccinations in Japan: Twitter Analysis
JMIR Infodemiology 2022;2(1):e32335
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| 381 | 16 | 30 | |
| 10.
Infodemic Management Using Digital Information and Knowledge Cocreation to Address COVID-19 Vaccine Hesitancy: Case Study From Ghana
JMIR Infodemiology 2022;2(2):e37134
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| 278 | 3 | 28 | |
| 11.
Charting the Information and Misinformation Landscape to Characterize Misinfodemics on Social Media: COVID-19 Infodemiology Study at a Planetary Scale
JMIR Infodemiology 2022;2(1):e32378
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| 480 | 72 | 28 | |
| 12.
COVID-19 and Vitamin D Misinformation on YouTube: Content Analysis
JMIR Infodemiology 2022;2(1):e32452
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| 522 | 118 | 27 | |
| 13.
Examining the Public’s Most Frequently Asked Questions Regarding COVID-19 Vaccines Using Search Engine Analytics in the United States: Observational Study
JMIR Infodemiology 2021;1(1):e28740
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| 153 | 29 | 27 | |
| 14.
Online Search Behavior Related to COVID-19 Vaccines: Infodemiology Study
JMIR Infodemiology 2021;1(1):e32127
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| 179 | 10 | 26 | |
| 15.
Large Language Models Can Enable Inductive Thematic Analysis of a Social Media Corpus in a Single Prompt: Human Validation Study
JMIR Infodemiology 2024;4(1):e59641
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| 970 | 2 | 26 | |
| 16.
Perceptions of Health Misinformation on Social Media: Cross-Sectional Survey Study
JMIR Infodemiology 2024;4(1):e51127
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| 3405 | 9 | 26 | |
| 17.
Health Care Providers’ Trusted Sources for Information About COVID-19 Vaccines: Mixed Methods Study
JMIR Infodemiology 2021;1(1):e33330
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| 255 | 11 | 24 | |
| 18.
The Impact of COVID-19 on Conspiracy Hypotheses and Risk Perception in Italy: Infodemiological Survey Study Using Google Trends
JMIR Infodemiology 2021;1(1):e29929
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| 158 | 19 | 22 | |
| 19.
Health Literacy, Equity, and Communication in the COVID-19 Era of Misinformation: Emergence of Health Information Professionals in Infodemic Management
JMIR Infodemiology 2022;2(1):e35014
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| 449 | 22 | 22 | |
| 20.
Examining Public Sentiments and Attitudes Toward COVID-19 Vaccination: Infoveillance Study Using Twitter Posts
JMIR Infodemiology 2022;2(1):e33909
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| 273 | 5 | 21 | |
| 21.
Public Attitudes and Factors of COVID-19 Testing Hesitancy in the United Kingdom and China: Comparative Infodemiology Study
JMIR Infodemiology 2021;1(1):e26895
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| 256 | 9 | 21 | |
| 22.
Exploring How Youth Use TikTok for Mental Health Information in British Columbia: Semistructured Interview Study With Youth
JMIR Infodemiology 2024;4(1):e53233
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| 3575 | 47 | 20 | |
| 23.
Advancing Infodemiology in a Digital Intensive Era
JMIR Infodemiology 2022;2(1):e37115
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| 410 | 32 | 20 | |
| 24.
Establishing Infodemic Management in Germany: A Framework for Social Listening and Integrated Analysis to Report Infodemic Insights at the National Public Health Institute
JMIR Infodemiology 2023;3(1):e43646
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| 1064 | 27 | 19 | |
| 25.
Characterization of Vaccine Tweets During the Early Stage of the COVID-19 Outbreak in the United States: Topic Modeling Analysis
JMIR Infodemiology 2021;1(1):e25636
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| 303 | 14 | 19 | |