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Desensitization to Fear-Inducing COVID-19 Health News on Twitter: Observational Study
JMIR Infodemiology 2021;1(1):e26876
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| 4 | 76 | 14 | |
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The Impact of the Online COVID-19 Infodemic on French Red Cross Actors’ Field Engagement and Protective Behaviors: Mixed Methods Study
JMIR Infodemiology 2021;1(1):e27472
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| 2 | 17 | 2 | |
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Change in Threads on Twitter Regarding Influenza, Vaccines, and Vaccination During the COVID-19 Pandemic: Artificial Intelligence–Based Infodemiology Study
JMIR Infodemiology 2021;1(1):e31983
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| 2 | 40 | 6 | |
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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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| 0 | 9 | 7 | |
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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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| 0 | 19 | 17 | |
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Sustained Reductions in Online Search Interest for Communicable Eye and Other Conditions During the COVID-19 Pandemic: Infodemiology Study
JMIR Infodemiology 2022;2(1):e31732
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| 0 | 5 | 1 | |
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Partisan Differences in Legislators’ Discussion of Vaccination on Twitter During the COVID-19 Era: Natural Language Processing Analysis
JMIR Infodemiology 2022;2(1):e32372
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| 0 | 29 | 4 | |
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Health Care Providers’ Trusted Sources for Information About COVID-19 Vaccines: Mixed Methods Study
JMIR Infodemiology 2021;1(1):e33330
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| 0 | 11 | 6 | |
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Factors Affecting Physicians’ Credibility on Twitter When Sharing Health Information: Online Experimental Study
JMIR Infodemiology 2022;2(1):e34525
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| 0 | 8 | 0 | |
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COVID-19 and Tweets About Quitting Cigarette Smoking: Topic Model Analysis of Twitter Posts 2018-2020
JMIR Infodemiology 2022;2(1):e36215
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| 0 | 16 | 1 | |
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The Role of Information Boxes in Search Engine Results for Symptom Searches: Analysis of Archival Data
JMIR Infodemiology 2022;2(2):e37286
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| 0 | 6 | 0 | |
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Web-Based Perspectives of Deemed Consent Organ Donation Legislation in Nova Scotia: Thematic Analysis of Commentary in Facebook Groups
JMIR Infodemiology 2022;2(2):e38242
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| 0 | 6 | 0 | |
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Negative COVID-19 Vaccine Information on Twitter: Content Analysis
JMIR Infodemiology 2022;2(2):e38485
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| 0 | 3 | 1 | |
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Monitoring Mentions of COVID-19 Vaccine Side Effects on Japanese and Indonesian Twitter: Infodemiological Study
JMIR Infodemiology 2022;2(2):e39504
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| 0 | 7 | 0 | |
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Exploring Chronic Pain and Pain Management Perspectives: Qualitative Pilot Analysis of Web-Based Health Community Posts
JMIR Infodemiology 2023;3(1):e41672
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| 0 | 2 | 0 | |
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The Early Detection of Fraudulent COVID-19 Products From Twitter Chatter: Data Set and Baseline Approach Using Anomaly Detection
JMIR Infodemiology 2023;3(1):e43694
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| 0 | 3 | 0 | |
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Themes Surrounding COVID-19 and Its Infodemic: Qualitative Analysis of the COVID-19 Discussion on the Multidisciplinary Healthcare Information for All Health Forum
JMIR Infodemiology 2022;2(1):e30167
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| 0 | 20 | 0 | |
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COVID-19 Information Sources and Health Behaviors During Pregnancy: Results From a Prenatal App-Embedded Survey
JMIR Infodemiology 2021;1(1):e31774
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| 0 | 20 | 1 | |
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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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| 0 | 72 | 7 | |
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Spread of COVID-19 Vaccine Misinformation in the Ninth Inning: Retrospective Observational Infodemic Study
JMIR Infodemiology 2022;2(1):e33587
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| 0 | 21 | 5 | |
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Skin Cancer Narratives on Instagram: Content Analysis
JMIR Infodemiology 2022;2(1):e34940
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| 0 | 11 | 2 | |
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Codeveloping and Evaluating a Campaign to Reduce Dementia Misconceptions on Twitter: Machine Learning Study
JMIR Infodemiology 2022;2(2):e36871
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| 0 | 13 | 0 | |
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Media Data and Vaccine Hesitancy: Scoping Review
JMIR Infodemiology 2022;2(2):e37300
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| 0 | 4 | 1 | |
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Characterizing the Discourse of Popular Diets to Describe Information Dispersal and Identify Leading Voices, Interaction, and Themes of Mental Health: Social Network Analysis
JMIR Infodemiology 2023;3(1):e38245
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| 0 | 14 | 0 | |
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The Information Sharing Behaviors of Dietitians and Twitter Users in the Nutrition and COVID-19 Infodemic: Content Analysis Study of Tweets
JMIR Infodemiology 2022;2(2):e38573
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| 0 | 5 | 1 | |