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Editorial (1)

Published on in Vol 2, No 1 (2022): Jan-Jun

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/37115, first published .
Advancing Infodemiology in a Digital Intensive Era

Advancing Infodemiology in a Digital Intensive Era

Advancing Infodemiology in a Digital Intensive Era

Authors of this article:

Tim Mackey1, 2 Author Orcid Image ;   Cynthia Baur3 Author Orcid Image ;   Gunther Eysenbach4, 5 Author Orcid Image
Article Authors Cited by (13) Tweetations (18) Metrics

Journals

  1. Deiner M, Kaur G, McLeod S, Schallhorn J, Chodosh J, Hwang D, Lietman T, Porco T. A Google Trends Approach to Identify Distinct Diurnal and Day-of-Week Web-Based Search Patterns Related to Conjunctivitis and Other Common Eye Conditions: Infodemiology Study. Journal of Medical Internet Research 2022;24(7):e27310 View
  2. Eysenbach G. Peer Review of “Are We Sure We Fully Understand What an Infodemic Is? A Global Perspective on Infodemiological Problems”. JMIRx Med 2022;3(3):e40822 View
  3. Stevens H, Rasul M, Oh Y. Emotions and Incivility in Vaccine Mandate Discourse: Natural Language Processing Insights. JMIR Infodemiology 2022;2(2):e37635 View
  4. Russell A, Valdez D, Chiang S, Montemayor B, Barry A, Lin H, Massey P. Using Natural Language Processing to Explore “Dry January” Posts on Twitter: Longitudinal Infodemiology Study. Journal of Medical Internet Research 2022;24(11):e40160 View
  5. Rovetta A, Castaldo L. Are We Sure We Fully Understand What an Infodemic Is? A Global Perspective on Infodemiological Problems. JMIRx Med 2022;3(3):e36510 View
  6. Yim D, Khuntia J, King E, Treskon M, Galiatsatos P. Expert Credibility and Sentiment in Infodemiology of Hydroxychloroquine’s Efficacy on Cable News Programs: Empirical Analysis. JMIR Infodemiology 2023;3:e45392 View
  7. Kamiński M, Czarny J, Skrzypczak P, Sienicki K, Roszak M. The Characteristics, Uses, and Biases of Studies Related to Malignancies Using Google Trends: Systematic Review. Journal of Medical Internet Research 2023;25:e47582 View
  8. Rovetta A. An integrated infoveillance approach using google trends and Talkwalker: Listening to web concerns about COVID-19 vaccines in Italy. Healthcare Analytics 2023;4:100272 View
  9. Haupt M, Chiu M, Chang J, Li Z, Cuomo R, Mackey T, Cresci S. Detecting nuance in conspiracy discourse: Advancing methods in infodemiology and communication science with machine learning and qualitative content coding. PLOS ONE 2023;18(12):e0295414 View
  10. Deiner M, Deiner N, Hristidis V, McLeod S, Doan T, Lietman T, Porco T. of large language models to assess likelihood of epidemics from content of Tweets: Infodemiology Study (Preprint). Journal of Medical Internet Research 2023 View
  11. Deiner M, Honcharov V, Li J, Mackey T, Porco T, Sarkar U. Large Language Models Can Enable Inductive Thematic Analysis of a Social Media Corpus in a Single Prompt: Human Validation Study. JMIR Infodemiology 2024;4:e59641 View
  12. Yan X, Li Z, Cao C, Huang L, Li Y, Meng X, Zhang B, Yu M, Huang T, Chen J, Li W, Hao L, Huang D, Yi B, Zhang M, Zha S, Yang H, Yao J, Qian P, Leung C, Fan H, Jiang P, Shui T. Characteristics, Influence, Prevention, and Control Measures of the Mpox Infodemic: Scoping Review of Infodemiology Studies. Journal of Medical Internet Research 2024;26:e54874 View
  13. Bragazzi N, Garbarino S. The Complex Interaction Between Sleep-Related Information, Misinformation, and Sleep Health: A Call for Comprehensive Research on Sleep Infodemiology and Infoveillance (Preprint). JMIR Infodemiology 2024 View