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

New Methods (944) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1641) Machine Learning (1465) Substance Abuse (419)

Published on in Vol 21, No 6 (2019): June

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/13803, first published .
A Machine Learning Approach for the Detection and Characterization of Illicit Drug Dealers on Instagram: Model Evaluation Study

A Machine Learning Approach for the Detection and Characterization of Illicit Drug Dealers on Instagram: Model Evaluation Study

A Machine Learning Approach for the Detection and Characterization of Illicit Drug Dealers on Instagram: Model Evaluation Study

Authors of this article:

Jiawei Li1, 2 Author Orcid Image ;   Qing Xu1, 2 Author Orcid Image ;   Neal Shah2 Author Orcid Image ;   Tim K Mackey1, 2, 3, 4 Author Orcid Image
Article Authors Cited by (49) Tweetations (41) Metrics

Journals

  1. Mackey T, Li J, Purushothaman V, Nali M, Shah N, Bardier C, Cai M, Liang B. Big Data, Natural Language Processing, and Deep Learning to Detect and Characterize Illicit COVID-19 Product Sales: Infoveillance Study on Twitter and Instagram. JMIR Public Health and Surveillance 2020;6(3):e20794 View
  2. 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
  3. 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
  4. Hu H, Phan N, Chun S, Geller J, Vo H, Ye X, Jin R, Ding K, Kenne D, Dou D. An insight analysis and detection of drug-abuse risk behavior on Twitter with self-taught deep learning. Computational Social Networks 2019;6(1) View
  5. Graham S, Huffer D, Blackadar J. Towards a Digital Sensorial Archaeology as an Experiment in Distant Viewing of the Trade in Human Remains on Instagram. Heritage 2020;3(2):208 View
  6. 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
  7. Xu Q, Shen Z, Shah N, Cuomo R, Cai M, Brown M, Li J, Mackey T. Characterizing Weibo Social Media Posts From Wuhan, China During the Early Stages of the COVID-19 Pandemic: Qualitative Content Analysis. JMIR Public Health and Surveillance 2020;6(4):e24125 View
  8. Petersen M, Petersen I, Poulsen C, Nørgaard L. #studydrugs–Persuasive posting on Instagram. International Journal of Drug Policy 2021;95:103100 View
  9. Sampa M, Hossain M, Hoque M, Islam R, Yokota F, Nishikitani M, Ahmed A. Blood Uric Acid Prediction With Machine Learning: Model Development and Performance Comparison. JMIR Medical Informatics 2020;8(10):e18331 View
  10. 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
  11. Manco L, Maffei N, Strolin S, Vichi S, Bottazzi L, Strigari L. Basic of machine learning and deep learning in imaging for medical physicists. Physica Medica 2021;83:194 View
  12. Hertig J, James S, Hummel C, Rubin M. Evaluation of pharmacists’ awareness of illegal online pharmacies and perceived impact on safe access to medicines. Medicine Access @ Point of Care 2021;5 View
  13. Cuomo R, Purushothaman V, Li J, Bardier C, Nali M, Shah N, Obradovich N, Yang J, Mackey T. Characterizing Self-Reported Tobacco, Vaping, and Marijuana-Related Tweets Geolocated for California College Campuses. Frontiers in Public Health 2021;9 View
  14. Piccialli F, di Cola V, Giampaolo F, Cuomo S. The Role of Artificial Intelligence in Fighting the COVID-19 Pandemic. Information Systems Frontiers 2021;23(6):1467 View
  15. Purushothaman V, Li J, Mackey T. Detecting Suicide and Self-Harm Discussions Among Opioid Substance Users on Instagram Using Machine Learning. Frontiers in Psychiatry 2021;12 View
  16. 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
  17. Ricard B, Hassanpour S. Deep Learning for Identification of Alcohol-Related Content on Social Media (Reddit and Twitter): Exploratory Analysis of Alcohol-Related Outcomes. Journal of Medical Internet Research 2021;23(9):e27314 View
  18. Alhabash S, Dong Y, Moureaud C, Muraro I, Hertig J. Effects of Fear and Humor Appeals in Public Service Announcements (PSAs) on Intentions to Purchase Medications via Social Media. International Journal of Environmental Research and Public Health 2022;19(19):12340 View
  19. Atsa’am D, Gbaden T, Wario R. Association Rules on Attributes of Illicit Drugs, Suspect’s Demographics and Offence Categories. Journal of Drug Issues 2023;53(4):637 View
  20. Lan H, Sha D, Malarvizhi A, Liu Y, Li Y, Meister N, Liu Q, Wang Z, Yang J, Yang C. COVID-Scraper: An Open-Source Toolset for Automatically Scraping and Processing Global Multi-Scale Spatiotemporal COVID-19 Records. IEEE Access 2021;9:84783 View
  21. Shah N, Nali M, Bardier C, Li J, Maroulis J, Cuomo R, Mackey T. Applying topic modelling and qualitative content analysis to identify and characterise ENDS product promotion and sales on Instagram. Tobacco Control 2023;32(e2):e153 View
  22. 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
  23. Xu Q, McMann T, Godinez H, Nali M, Li J, Cai M, Merenda C, Lee C, Araojo R, Mackey T. Impact of COVID-19 on HIV Prevention Access: A Multi-platform Social Media Infodemiology Study. AIDS and Behavior 2023;27(6):1886 View
  24. Barratt M, Lamy F, Engel L, Davies E, Puljevic C, Ferris J, Winstock A. Exploring Televend, an innovative combination of cryptomarket and messaging app technologies for trading prohibited drugs. Drug and Alcohol Dependence 2022;231:109243 View
  25. Moureaud C, Hertig J, Dong Y, Muraro I, Alhabash S. Purchase of prescription medicines via social media: A survey-based study of prevalence, risk perceptions, and motivations. Health Policy 2021;125(11):1421 View
  26. Xu Q, Nali M, McMann T, Godinez H, Li J, He Y, Cai M, Lee C, Merenda C, Araojo R, Mackey T. Unsupervised Machine Learning to Detect and Characterize Barriers to Pre-exposure Prophylaxis Therapy: Multiplatform Social Media Study. JMIR Infodemiology 2022;2(1):e35446 View
  27. 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
  28. Magliaro C, Ahluwalia A. Biomedical Research on Substances of Abuse: The Italian Case Study. Alternatives to Laboratory Animals 2022;50(6):423 View
  29. Gadhia S, Richards G, Marriott T, Rose J. Artificial intelligence and opioid use: a narrative review. BMJ Innovations 2023;9(2):78 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. Shacham E, Scroggins S, Ellis M. Implementing Geospatial Science and Technology to Get to Zero New HIV Infections. Current HIV/AIDS Reports 2023;20(3):139 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. Shin H, Yuniar C, Oh S, Purja S, Park S, Lee H, Kim E. The Adverse Effects and Nonmedical Use of Methylphenidate Before and After the Outbreak of COVID-19: Machine Learning Analysis. Journal of Medical Internet Research 2023;25:e45146 View
  34. 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
  35. Fuller A, Vasek M, Mariconti E, Johnson S. Understanding and preventing the advertisement and sale of illicit drugs to young people through social media: A multidisciplinary scoping review. Drug and Alcohol Review 2024;43(1):56 View
  36. Galvez-Hernandez P, Gonzalez-Viana A, Gonzalez-de Paz L, Shankardass K, Muntaner C. Generating Contextual Variables From Web-Based Data for Health Research: Tutorial on Web Scraping, Text Mining, and Spatial Overlay Analysis. JMIR Public Health and Surveillance 2024;10:e50379 View
  37. 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
  38. 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
  39. Al-Ghannam R, Ykhlef M, Al-Dossari H. Robust Drug Use Detection on X: Ensemble Method with a Transformer Approach. Arabian Journal for Science and Engineering 2024;49(9):12867 View
  40. Hu C, Liu B, Li X, Ye Y, Yin M. Knowledge-prompted ChatGPT: Enhancing drug trafficking detection on social media. Information & Management 2024;61(6):104010 View
  41. Wilkinson D, Hanley E, Knijnenburg B. A Comparative Analysis of Legislative Protections for Online Safety in the Global South: A Case Study of the Caribbean. Proceedings of the ACM on Human-Computer Interaction 2024;8(CSCW2):1 View

Books/Policy Documents

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  2. Bansod N, Kamble D, Mishra R, Kuliha M. Dark Web Pattern Recognition and Crime Analysis Using Machine Intelligence. View