Published on in Vol 20, No 4 (2018): April

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/10029, first published .
Solution to Detect, Classify, and Report Illicit Online Marketing and Sales of Controlled Substances via Twitter: Using Machine Learning and Web Forensics to Combat Digital Opioid Access

Solution to Detect, Classify, and Report Illicit Online Marketing and Sales of Controlled Substances via Twitter: Using Machine Learning and Web Forensics to Combat Digital Opioid Access

Solution to Detect, Classify, and Report Illicit Online Marketing and Sales of Controlled Substances via Twitter: Using Machine Learning and Web Forensics to Combat Digital Opioid Access

Journals

  1. Mackey T. Opioids and the Internet: Convergence of Technology and Policy to Address the Illicit Online Sales of Opioids. Health Services Insights 2018;11:117863291880099 View
  2. Zhao H, Muthupandi S, Kumara S. Managing Illicit Online Pharmacies: Web Analytics and Predictive Models Study. Journal of Medical Internet Research 2020;22(8):e17239 View
  3. Arillotta D, Schifano F, Napoletano F, Zangani C, Gilgar L, Guirguis A, Corkery J, Aguglia E, Vento A. Novel Opioids: Systematic Web Crawling Within the e-Psychonauts’ Scenario. Frontiers in Neuroscience 2020;14 View
  4. Miklosik A, Kuchta M, Evans N, Zak S. Towards the Adoption of Machine Learning-Based Analytical Tools in Digital Marketing. IEEE Access 2019;7:85705 View
  5. Penley B, Chen H, Eckel S, Ozawa S. Characteristics of online pharmacies selling Adderall. Journal of the American Pharmacists Association 2021;61(1):e103 View
  6. Anwar M, Khoury D, Aldridge A, Parker S, Conway K. Using Twitter to Surveil the Opioid Epidemic in North Carolina: An Exploratory Study. JMIR Public Health and Surveillance 2020;6(2):e17574 View
  7. Xu Q, Cai M, Mackey T. The illegal wildlife digital market: an analysis of Chinese wildlife marketing and sale on Facebook. Environmental Conservation 2020;47(3):206 View
  8. Li J, Xu Q, Shah N, Mackey T. A Machine Learning Approach for the Detection and Characterization of Illicit Drug Dealers on Instagram: Model Evaluation Study. Journal of Medical Internet Research 2019;21(6):e13803 View
  9. Han D, Lee S, Seo D. Using machine learning to predict opioid misuse among U.S. adolescents. Preventive Medicine 2020;130:105886 View
  10. Fittler A, Vida R, Káplár M, Botz L. Consumers Turning to the Internet Pharmacy Market: Cross-Sectional Study on the Frequency and Attitudes of Hungarian Patients Purchasing Medications Online. Journal of Medical Internet Research 2018;20(8):e11115 View
  11. Al-Rawi A. The fentanyl crisis & the dark side of social media. Telematics and Informatics 2019;45:101280 View
  12. Liang Y, Guo B, Yu Z, Zheng X, Wang Z, Tang L. A multi-view attention-based deep learning system for online deviant content detection. World Wide Web 2021;24(1):205 View
  13. Al-Rawi A. The convergence of social media and other communication technologies in the promotion of illicit and controlled drugs. Journal of Public Health 2020 View
  14. Raubenheimer J, Riordan B, Merrill J, Winter T, Ward R, Scarf D, Buckley N. Hey Google! will New Zealand vote to legalise cannabis? Using Google Trends data to predict the outcome of the 2020 New Zealand cannabis referendum. International Journal of Drug Policy 2021;90:103083 View
  15. Liang Y, Li H, Guo B, Yu Z, Zheng X, Samtani S, Zeng D. Fusion of heterogeneous attention mechanisms in multi-view convolutional neural network for text classification. Information Sciences 2021;548:295 View
  16. Vida R, Merczel S, Jáhn E, Fittler A. Developing a framework regarding a complex risk based methodology in the evaluation of hazards associated with medicinal products sourced via the internet. Saudi Pharmaceutical Journal 2020;28(12):1733 View
  17. 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
  18. ATALAY A. Sports Fans' Behaviors On Twitter: A Big Data Analysis of Sentiments 2018 World Cup Final Match. Spor Bilimleri Araştırmaları Dergisi 2021 View
  19. Jairoun A, Al-Hemyari S, Abdulla N, El-Dahiyat F, Jairoun M, AL-Tamimi S, Babar Z. Online medication purchasing during the Covid-19 pandemic: A pilot study from the United Arab Emirates. Journal of Pharmaceutical Policy and Practice 2021;14(1) View

Books/Policy Documents

  1. Baratto G. The Illegal Trade of Medicines on Social Media. View
  2. Holland B. Encyclopedia of Criminal Activities and the Deep Web. View
  3. Simran K, Balakrishna P, Vinayakumar R, Soman K. Security in Computing and Communications. View
  4. Peters W, Dehghantanha A, Parizi R, Srivastava G. Handbook of Big Data Privacy. View