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JMIR Infodemiology|October 5, 2022
Perspectives of the COVID-19 Pandemic on Reddit: Comparative Natural Language Processing Study of the United States, the United Kingdom, Canada, and AustraliaMengke Hu, Mike Conway
JMIR Infodemiology|February 22, 2022
Charting the Information and Misinformation Landscape to Characterize Misinfodemics on Social Media: COVID-19 Infodemiology Study at a Planetary ScaleEmily Chen, Julie Jiang, Ho-Chun Herbert Chang, et al.
JMIR Infodemiology|April 25, 2022
Examining Public Sentiments and Attitudes Toward COVID-19 Vaccination: Infoveillance Study Using Twitter PostsRanganathan Chandrasekaran, Rashi Desai, Harsh Shah, et al.
JMIR Infodemiology|April 4, 2023
Attitudes of Swedish Language Twitter Users Toward COVID-19 Vaccination: Exploratory Qualitative StudySafwat Beirakdar, Leon Klingborg, Sibylle Herzig van Wees
JMIR Infodemiology|April 28, 2023
Exploring Factors That Predict Marketing of e-Cigarette Products on Twitter: Infodemiology Approach Using Time SeriesNnamdi C Ezike, Allison Ames Boykin, Page D Dobbs, et al.
JMIR Infodemiology|April 28, 2023
Unsupervised Machine Learning to Detect and Characterize Barriers to Pre-exposure Prophylaxis Therapy: Multiplatform Social Media StudyQing Xu, Matthew C Nali, Tiana McMann, et al.
JMIR Infodemiology|April 28, 2023
Integrating Google Trends Search Engine Query Data Into Adult Emergency Department Volume Forecasting: Infodemiology StudyJesus Trevino, Sanjeev Malik, Michael Schmidt
JMIR Infodemiology|April 28, 2023
Public Figure Vaccination Rhetoric and Vaccine Hesitancy: Retrospective Twitter AnalysisVlad Honcharov, Jiawei Li, Maribel Sierra, et al.
JMIR Infodemiology|April 28, 2023
Lessons Learned From Interdisciplinary Efforts to Combat COVID-19 Misinformation: Development of Agile Integrative Methods From Behavioral Science, Data Science, and Implementation ScienceSahiti Myneni, Paula Cuccaro, Sarah Montgomery, et al.
JMIR Infodemiology|April 28, 2023
Predicting Patient Satisfaction With Medications for Treating Opioid Use Disorder: Case Study Applying Natural Language Processing to Reviews of Methadone and Buprenorphine/Naloxone on Health-Related Social MediaSamaneh Omranian, Maryam Zolnoori, Ming Huang, et al.
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