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Data Exploration and Classification of News Article Reliability: Deep Learning Study
JMIR Infodemiology 2022;2(2):e38839
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| 0 | 3 | 0 | |
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Emotions and Incivility in Vaccine Mandate Discourse: Natural Language Processing Insights
JMIR Infodemiology 2022;2(2):e37635
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| 0 | 12 | 0 | |
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Investigation of COVID-19 Misinformation in Arabic on Twitter: Content Analysis
JMIR Infodemiology 2022;2(2):e37007
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| 0 | 10 | 0 | |
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Correction: 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):e35012
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| 0 | 3 | 0 | |
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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 | 0 | |
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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 | 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 | 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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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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| 0 | 17 | 0 | |
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COVID-19 Misinformation Detection: Machine-Learned Solutions to the Infodemic
JMIR Infodemiology 2022;2(2):e38756
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| 0 | 7 | 0 | |
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Synthetic Cannabinoids in Prisons: Content Analysis of TikToks
JMIR Infodemiology 2022;2(1):e37632
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| 0 | 7 | 0 | |
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Perspectives of the COVID-19 Pandemic on Reddit: Comparative Natural Language Processing Study of the United States, the United Kingdom, Canada, and Australia
JMIR Infodemiology 2022;2(2):e36941
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| 0 | 6 | 0 | |
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Skin Cancer Narratives on Instagram: Content Analysis
JMIR Infodemiology 2022;2(1):e34940
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| 0 | 11 | 0 | |
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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 | 0 | |
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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 | 0 | |
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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 | 0 | |
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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 | 0 | |
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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 | 0 | |
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Direct-to-Consumer Genetic Testing on Social Media: Topic Modeling and Sentiment Analysis of YouTube Users' Comments
JMIR Infodemiology 2022;2(2):e38749
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| 0 | 5 | 0 | |
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Exploring Factors That Predict Marketing of e-Cigarette Products on Twitter: Infodemiology Approach Using Time Series
JMIR Infodemiology 2022;2(2):e37412
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| 0 | 3 | 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 | 0 | |
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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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Exploring Google Searches for Out-of-Clinic Medication Abortion in the United States During 2020: Infodemiology Approach Using Multiple Samples
JMIR Infodemiology 2022;2(1):e33184
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| 0 | 11 | 0 | |
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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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| 0 | 16 | 0 | |
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Temporal Variations and Spatial Disparities in Public Sentiment Toward COVID-19 and Preventive Practices in the United States: Infodemiology Study of Tweets
JMIR Infodemiology 2021;1(1):e31671
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| 0 | 5 | 0 | |