An unsupervised machine learning approach for the detection and characterization of illicit drug-dealing comments and interactions on Instagram-Reference-Cited by-同舟云学术

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An unsupervised machine learning approach for the detection and characterization of illicit drug-dealing comments and interactions on Instagram

Published:2021-07-02 Issue:1 Volume:43 Page:273-277
ISSN:0889-7077
Container-title:Substance Abuse
language:en
Short-container-title:Substance Abuse

Author:

Shah Neal¹^ORCID,Li Jiawei²³^ORCID,Mackey Tim K.¹²³⁴^ORCID

Affiliation:

1. Department of Healthcare Research and Policy, UC San Diego – Extension, San Diego, CA, USA

2. Global Health Policy and Data Institute, San Diego, CA, USA

3. S-3 Research LLC, San Diego, CA, USA

4. Department of Anesthesiology, University of California, San Diego School of Medicine, San Diego, CA, USA

Funder

National Institute on Drug Abuse

Publisher

Informa UK Limited

Subject

Psychiatry and Mental health,Medicine (miscellaneous)

Link

https://www.tandfonline.com/doi/pdf/10.1080/08897077.2021.1941508

Reference22 articles.

1. Opioids and the Internet: Convergence of Technology and Policy to Address the Illicit Online Sales of Opioids

2. Seaman I, Giraud-Carrier C. Prevalence and attitudes about illicit and prescription drugs on Twitter. Paper presented at: 2016 IEEE International Conference on Healthcare Informatics (ICHI), Chicago, IL, 2016:14–17.

3. #Drugsforsale: An exploration of the use of social media and encrypted messaging apps to supply and access drugs

4. Drug dealing on Facebook, Snapchat and Instagram: A qualitative analysis of novel drug markets in the Nordic countries

5. Opioid Discussion in the Twittersphere

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2. Technological barriers to creating regional resilience in digital platform‐based firms: Compound of performance sensitivity analysis and BIRCH algorithm;Thunderbird International Business Review;2024-02-06

3. Is This Safe? Examining Safety Assessments of Illicit Drug Purchasing on Social Media Using Conjoint Analysis;Substance Use & Misuse;2024-02-06

4. Detecting Relevant Information in High- Volume Chat Logs: Keyphrase Extraction for Grooming and Drug Dealing Forensic Analysis;2023 International Conference on Machine Learning and Applications (ICMLA);2023-12-15

5. Identification and Characterization of Illegal Sales of Cannabis and Nicotine Delivery Products on Telegram Messaging Platform;Nicotine and Tobacco Research;2023-12-14

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