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

Cyberpharmacies (40) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1573) Infodemiology and Infoveillance (1278) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1015) Pharmacovigilance (129)

Published on in Vol 17, No 12 (2015): December

Establishing a Link Between Prescription Drug Abuse and Illicit Online Pharmacies: Analysis of Twitter Data

Establishing a Link Between Prescription Drug Abuse and Illicit Online Pharmacies: Analysis of Twitter Data

Establishing a Link Between Prescription Drug Abuse and Illicit Online Pharmacies: Analysis of Twitter Data

Authors of this article:

Takeo Katsuki1 Author Orcid Image ;   Tim Ken Mackey2, 3, 4 Author Orcid Image ;   Raphael Cuomo4, 5 Author Orcid Image
Article Authors Cited by (67) Tweetations (44) Metrics

Journals

  1. Mavragani A. Infodemiology and Infoveillance: Scoping Review. Journal of Medical Internet Research 2020;22(4):e16206 View
  2. Smart R, Kase C, Taylor E, Lumsden S, Smith S, Stein B. Strengths and weaknesses of existing data sources to support research to address the opioids crisis. Preventive Medicine Reports 2020;17:101015 View
  3. 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
  4. Mackey T, Kalyanam J, Klugman J, Kuzmenko E, Gupta R. 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. Journal of Medical Internet Research 2018;20(4):e10029 View
  5. Mackey T, Kalyanam J, Katsuki T, Lanckriet G. Twitter-Based Detection of Illegal Online Sale of Prescription Opioid. American Journal of Public Health 2017;107(12):1910 View
  6. Sarker A, Gonzalez-Hernandez G, Ruan Y, Perrone J. Machine Learning and Natural Language Processing for Geolocation-Centric Monitoring and Characterization of Opioid-Related Social Media Chatter. JAMA Network Open 2019;2(11):e1914672 View
  7. Kalyanam J, Katsuki T, R.G. Lanckriet G, Mackey T. Exploring trends of nonmedical use of prescription drugs and polydrug abuse in the Twittersphere using unsupervised machine learning. Addictive Behaviors 2017;65:289 View
  8. Kim S, Marsch L, Hancock J, Das A. Scaling Up Research on Drug Abuse and Addiction Through Social Media Big Data. Journal of Medical Internet Research 2017;19(10):e353 View
  9. Chu K, Colditz J, Sidani J, Zimmer M, Primack B. Re-evaluating standards of human subjects protection for sensitive health data in social media networks. Social Networks 2021;67:41 View
  10. McLafferty S, Schneider D, Abelt K. Placing volunteered geographic health information: Socio-spatial bias in 311 bed bug report data for New York City. Health & Place 2020;62:102282 View
  11. Nicholson J, Marcum C, Higgins G. Predictors of Prescription Drug Misuse among High School Students in the United States. Deviant Behavior 2022;43(1):91 View
  12. Paul M, Dredze M. Social Monitoring for Public Health. Synthesis Lectures on Information Concepts, Retrieval, and Services 2017;9(5):1 View
  13. Carreiro S, Chai P, Carey J, Chapman B, Boyer E. Integrating Personalized Technology in Toxicology: Sensors, Smart Glass, and Social Media Applications in Toxicology Research. Journal of Medical Toxicology 2017;13(2):166 View
  14. Kalyanam J, Mackey T. A Review of Digital Surveillance Methods and Approaches to Combat Prescription Drug Abuse. Current Addiction Reports 2017;4(4):397 View
  15. Thaikla K, Pinyopornpanish K, Jiraporncharoen W, Angkurawaranon C. Cannabis and Kratom online information in Thailand: Facebook trends 2015–2016. Substance Abuse Treatment, Prevention, and Policy 2018;13(1) View
  16. Schwab-Reese L, Hovdestad W, Tonmyr L, Fluke J. The potential use of social media and other internet-related data and communications for child maltreatment surveillance and epidemiological research: Scoping review and recommendations. Child Abuse & Neglect 2018;85:187 View
  17. Burke-Garcia A, Stanton C. A tale of two tools: Reliability and feasibility of social media measurement tools examining e-cigarette twitter mentions. Informatics in Medicine Unlocked 2017;8:8 View
  18. Chou L, Chang K, Puspitasari I. Drug Abuse Research Trend Investigation with Text Mining. Computational and Mathematical Methods in Medicine 2020;2020:1 View
  19. Sarker A, DeRoos A, Perrone J. Mining social media for prescription medication abuse monitoring: a review and proposal for a data-centric framework. Journal of the American Medical Informatics Association 2020;27(2):315 View
  20. Pinyopornpanish K, Jiraporncharoen W, Thaikla K, Yoonut K, Angkurawaranon C. Sedative and Analgesic Drugs Online: A Content Analysis of the Supply and Demand Information Available in Thailand. Substance Use & Misuse 2018;53(4):641 View
  21. Daniulaityte R, Chen L, Lamy F, Carlson R, Thirunarayan K, Sheth A. “When ‘Bad’ is ‘Good’”: Identifying Personal Communication and Sentiment in Drug-Related Tweets. JMIR Public Health and Surveillance 2016;2(2):e162 View
  22. Myrseth H, Pallesen S, Torsheim T, Erevik E. Prevalence and correlates of stimulant and depressant pharmacological cognitive enhancement among Norwegian students. Nordic Studies on Alcohol and Drugs 2018;35(5):372 View
  23. Palamar J, Le A, Acosta P. Posting, Texting, and Related Social Risk Behavior While High. Substance Abuse 2020;41(3):382 View
  24. Guerra C, Mackey T. USA Criminal and Civil Prosecutions Associated with Illicit Online Pharmacies: Legal Analysis and Global Implications. Medicine Access @ Point of Care 2017;1:maapoc.0000020 View
  25. Mackey T, Kalyanam J. Detection of illicit online sales of fentanyls via Twitter. F1000Research 2017;6:1937 View
  26. Mackey T, Nayyar G. A review of existing and emerging digital technologies to combat the global trade in fake medicines. Expert Opinion on Drug Safety 2017;16(5):587 View
  27. Mackey T, Nayyar G. Digital danger: a review of the global public health, patient safety and cybersecurity threats posed by illicit online pharmacies. British Medical Bulletin 2016;118(1):110 View
  28. Zwier S. “Click for Closer Care”: A Content Analysis of Community Pharmacy Websites in Four Countries. Journal of Medical Internet Research 2017;19(6):e205 View
  29. 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
  30. Raghupathi V, Zhou Y, Raghupathi W. Exploring Big Data Analytic Approaches to Cancer Blog Text Analysis. International Journal of Healthcare Information Systems and Informatics 2019;14(4):1 View
  31. Zeraatkar K, Ahmadi M. Trends of infodemiology studies: a scoping review. Health Information & Libraries Journal 2018;35(2):91 View
  32. 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
  33. Suarez-Lledo V, Alvarez-Galvez J. Prevalence of Health Misinformation on Social Media: Systematic Review. Journal of Medical Internet Research 2021;23(1):e17187 View
  34. Guirguis A, Moosa I, Gittins R, Schifano F. What About Drug Checking? Systematic Review and Netnographic Analysis of Social Media. Current Neuropharmacology 2020;18(10):906 View
  35. Assaf R, Young K. Trends in Pediatric Recreational Drug Use and Ingestions. Advances in Pediatrics 2021;68:261 View
  36. Wright A, Jones C, Chau D, Matthew Gladden R, Sumner S. Detection of emerging drugs involved in overdose via diachronic word embeddings of substances discussed on social media. Journal of Biomedical Informatics 2021;119:103824 View
  37. Lamsal R, Harwood A, Read M. Socially Enhanced Situation Awareness from Microblogs Using Artificial Intelligence: A Survey. ACM Computing Surveys 2023;55(4):1 View
  38. Zhai S, Li Y, Chi M. The Impact of Government Social Media Information Quality on Public Panic During the Infodemic. Frontiers in Psychology 2022;13 View
  39. Soboleva M, Loskutova E, Kosova I. Pharmacoepidemiological study of the use of e-pharmacies by the population. Journal Of Advanced Pharmacy Education And Research 2022;12(3):36 View
  40. Sumner S, Bowen D, Holland K, Zwald M, Vivolo-Kantor A, Guy G, Heuett W, Pressley D, Jones C. Estimating Weekly National Opioid Overdose Deaths in Near Real Time Using Multiple Proxy Data Sources. JAMA Network Open 2022;5(7):e2223033 View
  41. Li S, Swortwood M, Yu J. Determination of morphine, codeine, and thebaine concentrations from poppy seed tea using magnetic carbon nanotubes facilitated dispersive micro-solid phase extraction and GC-MS analysis. Forensic Science International 2021;329:111052 View
  42. 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
  43. Pashkov V, Soloviov O, Harkusha A. Digital Marketing: Problems of Internet Pharmacies Legal Regulation. SOCRATES. Rīgas Stradiņa universitātes Juridiskās fakultātes elektroniskais juridisko zinātnisko rakstu žurnāls / SOCRATES. Rīga Stradiņš University Faculty of Law Electronic Scientific Journal of Law 2021;3(21):191 View
  44. Pashkov V, Soloviov O, Harkusha A. LEGAL CHARACTERISTICS OF PHARMACEUTICAL ACTIVITY UNDER THE EMERGENCY CONDITIONS: PANDEMIC AND WAR. Wiadomości Lekarskie 2022;75(9):2286 View
  45. Bremer W, Plaisance K, Walker D, Bonn M, Love J, Perrone J, Sarker A. Barriers to opioid use disorder treatment: A comparison of self-reported information from social media with barriers found in literature. Frontiers in Public Health 2023;11 View
  46. Limbu Y, Huhmann B. Illicit Online Pharmacies: A Scoping Review. International Journal of Environmental Research and Public Health 2023;20(9):5748 View
  47. 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
  48. Parker M, Valdez D, Rao V, Eddens K, Agley J. Results and Methodological Implications of the Digital Epidemiology of Prescription Drug References Among Twitter Users: Latent Dirichlet Allocation (LDA) Analyses. Journal of Medical Internet Research 2023;25:e48405 View
  49. Palomino K, Berdugo C, Vélez J, Belo V. Leading consumption patterns of psychoactive substances in Colombia: A deep neural network-based clustering-oriented embedding approach. PLOS ONE 2023;18(8):e0290098 View
  50. Carabot F, Donat-Vargas C, Santoma-Vilaclara J, Ortega M, García-Montero C, Fraile-Martínez O, Zaragoza C, Monserrat J, Alvarez-Mon M, Alvarez-Mon M. Exploring Perceptions About Paracetamol, Tramadol, and Codeine on Twitter Using Machine Learning: Quantitative and Qualitative Observational Study. Journal of Medical Internet Research 2023;25:e45660 View
  51. Kim D, Soloviov O. Rebuilding Ukraine - the Case of the Health Sector. SSRN Electronic Journal 2024 View
  52. Hakariya H, Yokoyama N, Lee J, Hakariya A, Ikejiri T. Illicit Trade of Prescription Medications Through X (Formerly Twitter) in Japan: Cross-Sectional Study. JMIR Formative Research 2024;8:e54023 View

Books/Policy Documents

  1. Del Vigna F, Petrocchi M, Tommasi A, Zavattari C, Tesconi M. Social Informatics. View
  2. Spitzberg B, Tsou M, Jung C. The Handbook of Applied Communication Research. View
  3. Baratto G. The Illegal Trade of Medicines on Social Media. View
  4. Del Vigna F, Avvenuti M, Bacciu C, Deluca P, Petrocchi M, Marchetti A, Tesconi M. Advances in Intelligent Data Analysis XV. View
  5. Baratto G. The Illegal Trade of Medicines on Social Media. View
  6. Mejova Y. Handbook of Computational Social Science for Policy. View
  7. Raghupathi V, Zhou Y, Raghupathi W. Research Anthology on Big Data Analytics, Architectures, and Applications. View