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Synthetic Cannabinoids in Prisons: Content Analysis of TikToks

JMIR Infodemiology 2022;2(1):e37632

4743 9 3
Corpus-Based Discourse Analysis of a Reddit Community of Users of Crystal Methamphetamine: Mixed Methods Study

JMIR Infodemiology 2023;3(1):e48189

2303 12 0
Misinformation About and Interest in Chlorine Dioxide During the COVID-19 Pandemic in Mexico Identified Using Google Trends Data: Infodemiology Study

JMIR Infodemiology 2022;2(1):e29894

2259 24 5
TikTok as a Source of Health Information and Misinformation for Young Women in the United States: Survey Study

JMIR Infodemiology 2024;4(1):e54663

2124 6 4
Exploring How Youth Use TikTok for Mental Health Information in British Columbia: Semistructured Interview Study With Youth

JMIR Infodemiology 2024;4(1):e53233

1046 47 2
Measuring the Burden of Infodemics: Summary of the Methods and Results of the Fifth WHO Infodemic Management Conference

JMIR Infodemiology 2023;3(1):e44207

1040 153 22
The Role of Social Media in Health Misinformation and Disinformation During the COVID-19 Pandemic: Bibliometric Analysis

JMIR Infodemiology 2023;3(1):e48620

1038 7 12
A Public Health Research Agenda for Managing Infodemics: Methods and Results of the First WHO Infodemiology Conference

JMIR Infodemiology 2021;1(1):e30979

991 271 84
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

886 27 11
Perceptions of Health Misinformation on Social Media: Cross-Sectional Survey Study

JMIR Infodemiology 2024;4(1):e51127

790 9 3
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

680 116 50
Evaluating the Influence of Role-Playing Prompts on ChatGPT’s Misinformation Detection Accuracy: Quantitative Study

JMIR Infodemiology 2024;4(1):e60678

606 0 1
Reproductive Health Experiences Shared on TikTok by Young People: Content Analysis

JMIR Infodemiology 2023;3(1):e42810

587 6 4
Monitoring Depression Trends on Twitter During the COVID-19 Pandemic: Observational Study

JMIR Infodemiology 2021;1(1):e26769

581 17 61
Investigating COVID-19 Vaccine Communication and Misinformation on TikTok: Cross-sectional Study

JMIR Infodemiology 2022;2(2):e38316

527 28 10
Ethical Considerations in Infodemic Management: Systematic Scoping Review

JMIR Infodemiology 2024;4(1):e56307

523 8 2
Advertising Alternative Cancer Treatments and Approaches on Meta Social Media Platforms: Content Analysis

JMIR Infodemiology 2023;3(1):e43548

517 157 6
Desensitization to Fear-Inducing COVID-19 Health News on Twitter: Observational Study

JMIR Infodemiology 2021;1(1):e26876

492 76 30
Using Machine Learning Technology (Early Artificial Intelligence–Supported Response With Social Listening Platform) to Enhance Digital Social Understanding for the COVID-19 Infodemic: Development and Implementation Study

JMIR Infodemiology 2023;3(1):e47317

466 3 6
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

458 2 1
Global Misinformation Spillovers in the Vaccination Debate Before and During the COVID-19 Pandemic: Multilingual Twitter Study

JMIR Infodemiology 2023;3(1):e44714

449 31 5
Identifying Frames of the COVID-19 Infodemic: Thematic Analysis of Misinformation Stories Across Media

JMIR Infodemiology 2022;2(1):e33827

447 8 10
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

445 14 4
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

425 3 0
Public Figure Vaccination Rhetoric and Vaccine Hesitancy: Retrospective Twitter Analysis

JMIR Infodemiology 2023;3(1):e40575

393 7 6

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