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

Infodemiology and Infoveillance (1349) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1641) Substance Abuse (419) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1041) Machine Learning (1465)

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

Authors of this article:

Tim Mackey1 Author Orcid Image ;   Janani Kalyanam2 Author Orcid Image ;   Josh Klugman3 Author Orcid Image ;   Ella Kuzmenko3 Author Orcid Image ;   Rashmi Gupta4 Author Orcid Image
Article Authors Cited by (62) Tweetations (30) Metrics

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 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 2022;44(1):e153 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' Behavior on Twitter: A Big Data Analysis of Sentiments in the 2018 World Cup Final. Spor Bilimleri Araştırmaları Dergisi 2021;6(1):62 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
  20. Shah N, Li J, Mackey T. An Unsupervised Machine Learning Approach for the Detection and Characterization of Illicit Drug-Dealing Comments and Interactions on Instagram. Substance Abuse 2022;43(1):273 View
  21. Hu C, Yin M, Liu B, Li X, Ye Y. Identifying Illicit Drug Dealers on Instagram with Large-scale Multimodal Data Fusion. ACM Transactions on Intelligent Systems and Technology 2021;12(5):1 View
  22. Haupt M, Cuomo R, Li J, Nali M, Mackey T. The influence of social media affordances on drug dealer posting behavior across multiple social networking sites (SNS). Computers in Human Behavior Reports 2022;8:100235 View
  23. Hu C, Liu B, Ye Y, Li X. Fine-grained classification of drug trafficking based on Instagram hashtags. Decision Support Systems 2023;165:113896 View
  24. Sullivan H, O'Donoghue A, Mannis S, Carpenter A. Character-space-limited online prescription drug communications: Four experimental studies. Research in Social and Administrative Pharmacy 2022;18(12):4092 View
  25. Gadhia S, Richards G, Marriott T, Rose J. Artificial intelligence and opioid use: a narrative review. BMJ Innovations 2023;9(2):78 View
  26. Sansone A, Cuzin B, Jannini E. Facing Counterfeit Medications in Sexual Medicine. A Systematic Scoping Review on Social Strategies and Technological Solutions. Sexual Medicine 2021;9(6):100437 View
  27. Delir Haghighi P, Burstein F, Urquhart D, Cicuttini F. Investigating Individuals’ Perceptions Regarding the Context Around the Low Back Pain Experience: Topic Modeling Analysis of Twitter Data. Journal of Medical Internet Research 2021;23(12):e26093 View
  28. Long C, Kumaran H, Goh K, Bakrin F, Ming L, Rehman I, Dhaliwal J, Hadi M, Sim Y, Tan C. Online Pharmacies Selling Prescription Drugs: Systematic Review. Pharmacy 2022;10(2):42 View
  29. Coombs T, Abdelkader A, Ginige T, Van Calster P, Assi S. Understanding synthetic drug analogues among the homeless population from the perspectives of the public: thematic analysis of Twitter data. Journal of Substance Use 2024;29(4):501 View
  30. Nam K, Shin H, Bae B, Kim E. Survival of Illegal Fentanyl Sales in the Twittersphere and Tumblr Sphere: A Cross-Sectional Forensics Approach. Drug Targets and Therapeutics 2023;2(1):62 View
  31. Kasson E, Filiatreau L, Kaiser N, Davet K, Taylor J, Garg S, El Sherief M, Aledavood T, De Choudhury M, Cavazos-Rehg P. Using Social Media to Examine Themes Surrounding Fentanyl Misuse and Risk Indicators. Substance Use & Misuse 2023;58(7):920 View
  32. Limbu Y, Huhmann B. Illicit Online Pharmacies: A Scoping Review. International Journal of Environmental Research and Public Health 2023;20(9):5748 View
  33. Raza S, Schwartz B, Lakamana S, Ge Y, Sarker A. A framework for multi-faceted content analysis of social media chatter regarding non-medical use of prescription medications. BMC Digital Health 2023;1(1) View
  34. Luca M, Campedelli G, Centellegher S, Tizzoni M, Lepri B. Crime, inequality and public health: a survey of emerging trends in urban data science. Frontiers in Big Data 2023;6 View
  35. Nali M, McMann T, Purushothaman V, Li Z, Cuomo R, Liang B, Mackey T. Assessing Characteristics and Compliance of Online Delta-8 Tetrahydrocannabinol Product Sellers. Cannabis and Cannabinoid Research 2024;9(4):e1132 View
  36. Boehnke J, Loupos P, Gu Y. Social drug dealing: how peer-to-peer fintech platforms have transformed illicit drug markets. Annals of Operations Research 2024;335(2):645 View
  37. 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
  38. Al-Hamid A, Tudor C, Assi S. Exploring profile, effects and toxicity of novel synthetic opioids and classical opioids via Twitter: A qualitative study. Emerging Trends in Drugs, Addictions, and Health 2024;4:100139 View
  39. 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
  40. Nali M, Purushothaman V, Li Z, Larsen M, Cuomo R, Yang J, Mackey T. Identification and Characterization of Illegal Sales of Cannabis and Nicotine Delivery Products on Telegram Messaging Platform. Nicotine and Tobacco Research 2024;26(6):771 View
  41. Haupt M, Cuomo R, Cui M, Mackey T. Is This Safe? Examining Safety Assessments of Illicit Drug Purchasing on Social Media Using Conjoint Analysis. Substance Use & Misuse 2024;59(7):999 View
  42. Castillo-Toledo C, Fraile-Martínez O, Donat-Vargas C, Lara-Abelenda F, Ortega M, Garcia-Montero C, Mora F, Alvarez-Mon M, Quintero J, Alvarez-Mon M. Insights from the Twittersphere: a cross-sectional study of public perceptions, usage patterns, and geographical differences of tweets discussing cocaine. Frontiers in Psychiatry 2024;15 View
  43. Browne T, Abedin M, Chowdhury M. A systematic review on research utilising artificial intelligence for open source intelligence (OSINT) applications. International Journal of Information Security 2024;23(4):2911 View
  44. Almeida A, Patton T, Conway M, Gupta A, Strathdee S, Bórquez A. The Use of Natural Language Processing Methods in Reddit to Investigate Opioid Use: Scoping Review. JMIR Infodemiology 2024;4:e51156 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