This paper is in the following e-collection/theme issue:

Opioid and Related Substance Abuse Crisis (96) Infodemiology and Infoveillance (1167) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (946) Surveillance Reports (100)

Published on in Vol 6, No 2 (2020): Apr-Jun

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/17574, first published .
Using Twitter to Surveil the Opioid Epidemic in North Carolina: An Exploratory Study

Using Twitter to Surveil the Opioid Epidemic in North Carolina: An Exploratory Study

Using Twitter to Surveil the Opioid Epidemic in North Carolina: An Exploratory Study

Authors of this article:

Mohd Anwar 1 Author Orcid Image ;   Dalia Khoury 2 Author Orcid Image ;   Arnie P Aldridge 2 Author Orcid Image ;   Stephanie J Parker 2 Author Orcid Image ;   Kevin P Conway 2 Author Orcid Image
Article Authors Cited by (12) Tweetations (20) Metrics

Journals

  1. Marks C, Carrasco-Escobar G, Carrasco-Hernández R, Johnson D, Ciccarone D, Strathdee S, Smith D, Bórquez A. Methodological approaches for the prediction of opioid use-related epidemics in the United States: a narrative review and cross-disciplinary call to action. Translational Research 2021;234:88 View
  2. Tacheva Z, Ivanov A. Exploring the Association Between the “Big Five” Personality Traits and Fatal Opioid Overdose: County-Level Empirical Analysis. JMIR Mental Health 2021;8(3):e24939 View
  3. Khoury D, Preiss A, Geiger P, Anwar M, Conway K. Increases in Naloxone Administrations by Emergency Medical Services Providers During the COVID-19 Pandemic: Retrospective Time Series Study. JMIR Public Health and Surveillance 2021;7(5):e29298 View
  4. Bushman M, Godishala S, Hyzer R, Jerisha J, Jolliff A, Kaji E, Kerr B, Mathur A, Tsao O. Adolescent Health on Social Media and the Mentorship of Youth Investigators: Five Content Analysis Studies Conducted by Youth Investigators. JMIR Mental Health 2021;8(9):e29318 View
  5. Gadhia S, Richards G, Marriott T, Rose J. Artificial intelligence and opioid use: a narrative review. BMJ Innovations 2023;9(2):78 View
  6. Lane J, Habib D, Curtis B. Linguistic Methodologies to Surveil the Leading Causes of Mortality: Scoping Review of Twitter for Public Health Data. Journal of Medical Internet Research 2023;25:e39484 View
  7. Patton T, Abramovitz D, Johnson D, Leas E, Nobles A, Caputi T, Ayers J, Strathdee S, Bórquez A. Characterizing Help-Seeking Searches for Substance Use Treatment From Google Trends and Assessing Their Use for Infoveillance: Longitudinal Descriptive and Validation Statistical Analysis. Journal of Medical Internet Research 2022;24(12):e41527 View
  8. Carabot F, Fraile-Martínez O, Donat-Vargas C, Santoma J, Garcia-Montero C, Pinto da Costa M, Molina-Ruiz R, Ortega M, Alvarez-Mon M, Alvarez-Mon M. Understanding Public Perceptions and Discussions on Opioids Through Twitter: Cross-Sectional Infodemiology Study. Journal of Medical Internet Research 2023;25:e50013 View
  9. Giorgi S, Yaden D, Eichstaedt J, Ungar L, Schwartz H, Kwarteng A, Curtis B. Predicting U.S. county opioid poisoning mortality from multi-modal social media and psychological self-report data. Scientific Reports 2023;13(1) View
  10. Tang L, Korona-Bailey J, Zaras D, Roberts A, Mukhopadhyay S, Espy S, Walsh C. Using Natural Language Processing to Predict Fatal Drug Overdose From Autopsy Narrative Text: Algorithm Development and Validation Study. JMIR Public Health and Surveillance 2023;9:e45246 View
  11. Carabot F, Donat-Vargas C, Santoma-Vilaclara J, Ortega M, García-Montero C, Fraile-Martínez O, Zaragoza C, Monserrat J, Alvarez-Mon M, Alvarez-Mon M. Exploring Perceptions About Paracetamol, Tramadol, and Codeine on Twitter Using Machine Learning: Quantitative and Qualitative Observational Study. Journal of Medical Internet Research 2023;25:e45660 View