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Citing this Article

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Published on 27.04.18 in Vol 20, No 4 (2018): April

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

Works citing "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"

According to Crossref, the following articles are citing this article (DOI 10.2196/10029):

(note that this is only a small subset of citations)

  1. Han D, Lee S, Seo D. Using machine learning to predict opioid misuse among U.S. adolescents. Preventive Medicine 2020;130:105886
  2. Li J, Xu Q, Shah N, Mackey TK. 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
  3. 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
  4. Al-Rawi A. The fentanyl crisis & the dark side of social media. Telematics and Informatics 2019;45:101280
  5. Mackey TK. Opioids and the Internet: Convergence of Technology and Policy to Address the Illicit Online Sales of Opioids. Health Services Insights 2018;11:117863291880099
  6. Fittler A, Vida RG, 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

According to Crossref, the following books are citing this article (DOI 10.2196/10029)

  1. Holland BJ. Encyclopedia of Criminal Activities and the Deep Web. 2020. chapter 7:108