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

Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1641) Infodemiology and Infoveillance (1349) Natural Language Processing (692) Ontologies, Classifications, and Coding (239) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1041) Opioid and Related Substance Misuse (147) Substance Abuse (419)

Published on in Vol 22, No 8 (2020): August

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/18350, first published .
Social Media Text Mining Framework for Drug Abuse: Development and Validation Study With an Opioid Crisis Case Analysis

Social Media Text Mining Framework for Drug Abuse: Development and Validation Study With an Opioid Crisis Case Analysis

Social Media Text Mining Framework for Drug Abuse: Development and Validation Study With an Opioid Crisis Case Analysis

Authors of this article:

Tareq Nasralah1 Author Orcid Image ;   Omar El-Gayar2 Author Orcid Image ;   Yong Wang3 Author Orcid Image
Article Authors Cited by (15) Tweetations (4) Metrics

Journals

  1. Singh T, Roberts K, Cohen T, Cobb N, Wang J, Fujimoto K, Myneni S. Social Media as a Research Tool (SMaaRT) for Risky Behavior Analytics: Methodological Review. JMIR Public Health and Surveillance 2020;6(4):e21660 View
  2. Li Z, Du X, Liao X, Jiang X, Champagne-Langabeer T. Demystifying the Dark Web Opioid Trade: Content Analysis on Anonymous Market Listings and Forum Posts. Journal of Medical Internet Research 2021;23(2):e24486 View
  3. Rosário-Ferreira N, Marques-Pereira C, Pires M, Ramalhão D, Pereira N, Guimarães V, Santos Costa V, Moreira I. The Treasury Chest of Text Mining: Piling Available Resources for Powerful Biomedical Text Mining. BioChem 2021;1(2):60 View
  4. Abhinav Potineni . Inexpensive Detection of Substance Abuse Based on Social Media Data using Machine Learning. International Journal of Scientific Research in Computer Science, Engineering and Information Technology 2022:01 View
  5. Calac A, McMann T, Cai M, Li J, Cuomo R, Mackey T. Exploring substance use disorder discussions in Native American communities: a retrospective Twitter infodemiology study. Harm Reduction Journal 2022;19(1) View
  6. Dipietro L, Gonzalez-Mego P, Ramos-Estebanez C, Zukowski L, Mikkilineni R, Rushmore R, Wagner T. The evolution of Big Data in neuroscience and neurology. Journal of Big Data 2023;10(1) View
  7. Arillotta D, Floresta G, Guirguis A, Corkery J, Catalani V, Martinotti G, Sensi S, Schifano F. GLP-1 Receptor Agonists and Related Mental Health Issues; Insights from a Range of Social Media Platforms Using a Mixed-Methods Approach. Brain Sciences 2023;13(11):1503 View
  8. Kanan T, AbedAlghafer A, AlZu'bi S, Hawashin B, Mughaid A, Kanaan G, Kamruzzaman M. An Intelligent Health Care System for Detecting Drug Abuse in Social Media Platforms Based on Low Resource Language. IEEE/ACM Transactions on Audio, Speech, and Language Processing 2024;32:691 View
  9. Kilpeläinen K, Ståhl T, Ylöstalo T, Keski-Kuha T, Nyrhinen R, Koponen P, Gissler M. Citizens’ digital footprints to support health promotion at the local level—PUHTI study, Finland. European Journal of Public Health 2024;34(4):676 View
  10. Yuan Y, Kasson E, Taylor J, Cavazos-Rehg P, De Choudhury M, Aledavood T. Examining the Gateway Hypothesis and Mapping Substance Use Pathways on Social Media: Machine Learning Approach. JMIR Formative Research 2024;8:e54433 View
  11. Rao V, Valdez D, Muralidharan R, Agley J, Eddens K, Dendukuri A, Panth V, Parker M. Digital Epidemiology of Prescription Drug References on X (Formerly Twitter): Neural Network Topic Modeling and Sentiment Analysis. Journal of Medical Internet Research 2024;26:e57885 View

Books/Policy Documents

  1. Nacheva R. Advances in Econometrics, Operational Research, Data Science and Actuarial Studies. View
  2. Thomas A, Bakshi S, Rockas M. Technology-Assisted Interventions for Substance Use Disorders. View
  3. Ankita , Garg R. Data Science and Applications. View