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Identifying Illicit Drug Dealers on Instagram with Large-scale Multimodal Data Fusion

Authors:

Yanfang YeAuthors Info & Claims

ACM Transactions on Intelligent Systems and Technology (TIST), Volume 12, Issue 5

Article No.: 59, Pages 1 - 23

https://doi.org/10.1145/3472713

Published: 23 September 2021 Publication History

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Abstract

Illicit drug trafficking via social media sites such as Instagram have become a severe problem, thus drawing a great deal of attention from law enforcement and public health agencies. How to identify illicit drug dealers from social media data has remained a technical challenge for the following reasons. On the one hand, the available data are limited because of privacy concerns with crawling social media sites; on the other hand, the diversity of drug dealing patterns makes it difficult to reliably distinguish drug dealers from common drug users. Unlike existing methods that focus on posting-based detection, we propose to tackle the problem of illicit drug dealer identification by constructing a large-scale multimodal dataset named Identifying Drug Dealers on Instagram (IDDIG). Nearly 4,000 user accounts, of which more than 1,400 are drug dealers, have been collected from Instagram with multiple data sources including post comments, post images, homepage bio, and homepage images. We then design a quadruple-based multimodal fusion method to combine the multiple data sources associated with each user account for drug dealer identification. Experimental results on the constructed IDDIG dataset demonstrate the effectiveness of the proposed method in identifying drug dealers (almost 95% accuracy). Moreover, we have developed a hashtag-based community detection technique for discovering evolving patterns, especially those related to geography and drug types.

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Haupt MCuomo RCui MMackey T(2024)Is This Safe? Examining Safety Assessments of Illicit Drug Purchasing on Social Media Using Conjoint AnalysisSubstance Use & Misuse10.1080/10826084.2024.231050759:7(999-1011)Online publication date: 6-Feb-2024
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Hu CLiu BLi XYe YYin M(2024)Knowledge-prompted ChatGPT: Enhancing drug trafficking detection on social mediaInformation & Management10.1016/j.im.2024.10401061:6(104010)Online publication date: Sep-2024
https://doi.org/10.1016/j.im.2024.104010
Fuller AVasek MMariconti EJohnson S(2023)Understanding and preventing the advertisement and sale of illicit drugs to young people through social media: A multidisciplinary scoping reviewDrug and Alcohol Review10.1111/dar.1371643:1(56-74)Online publication date: 31-Jul-2023
https://doi.org/10.1111/dar.13716
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Index Terms

Identifying Illicit Drug Dealers on Instagram with Large-scale Multimodal Data Fusion
1. Applied computing
  1. Law, social and behavioral sciences
2. Information systems
  1. Information systems applications
    1. Data mining

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cover image ACM Transactions on Intelligent Systems and Technology

ACM Transactions on Intelligent Systems and Technology Volume 12, Issue 5

October 2021

383 pages

ISSN:2157-6904

EISSN:2157-6912

DOI:10.1145/3484925

Editor:
Huan Liu
Arizona State University, USA

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Publication History

Published: 23 September 2021

Accepted: 01 June 2021

Revised: 01 May 2021

Received: 01 December 2020

Published in TIST Volume 12, Issue 5

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https://doi.org/10.1080/10826084.2024.2310507
Hu CLiu BLi XYe YYin M(2024)Knowledge-prompted ChatGPT: Enhancing drug trafficking detection on social mediaInformation & Management10.1016/j.im.2024.10401061:6(104010)Online publication date: Sep-2024
https://doi.org/10.1016/j.im.2024.104010
Fuller AVasek MMariconti EJohnson S(2023)Understanding and preventing the advertisement and sale of illicit drugs to young people through social media: A multidisciplinary scoping reviewDrug and Alcohol Review10.1111/dar.1371643:1(56-74)Online publication date: 31-Jul-2023
https://doi.org/10.1111/dar.13716
Alves JPedroso HVenetikides RKöster JGrochocki LFreitas CBarddal J(2023)Detecting Relevant Information in High- Volume Chat Logs: Keyphrase Extraction for Grooming and Drug Dealing Forensic Analysis2023 International Conference on Machine Learning and Applications (ICMLA)10.1109/ICMLA58977.2023.00299(1979-1985)Online publication date: 15-Dec-2023
https://doi.org/10.1109/ICMLA58977.2023.00299
Hu CLiu BYe YLi X(2023)Fine-grained classification of drug trafficking based on Instagram hashtagsDecision Support Systems10.1016/j.dss.2022.113896165:COnline publication date: 1-Feb-2023
https://dl.acm.org/doi/10.1016/j.dss.2022.113896
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