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Social drug dealing: how peer-to-peer fintech platforms have transformed illicit drug markets

Author

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  • Jörn Boehnke

    (University of California Davis)

  • Pantelis Loupos

    (University of California Davis)

  • Ying Gu

    (University of Washington)

Abstract

Digital platforms have revolutionized the way illegal drug trafficking is taking place. Modern drug dealers use social network platforms, such as Instagram and TikTok, as direct-to-consumer marketing tools. But apart from the marketing side, drug dealers also use fintech payment apps to engage in financial transactions with their clients. In this work, we leverage a large dataset from Venmo to investigate the digital money trail of drug dealers and the social networks they create. Using text and social network analytics, we identify two types of illicit users: mixed-activity participants and heavy drug traffickers and build a random forest classifier that accurately predicts both types of illicit nodes. We then investigate the social network structure of drug dealers on Venmo and find that heavy drug traffickers share similar network characteristics with previous literature findings on drug trafficking networks. However, mixed-activity participants exhibit different patterns of network structure characteristics, including a higher clustering coefficient, suggesting that they may be accessing multiple networks and bridging those networks through their illicit activities. Our findings highlight the importance of distinguishing between these two types of illicit users and provide law enforcement agencies with valuable insights that can aid in combating illegal drug transactions in digital payment apps.

Suggested Citation

  • Jörn Boehnke & Pantelis Loupos & Ying Gu, 2024. "Social drug dealing: how peer-to-peer fintech platforms have transformed illicit drug markets," Annals of Operations Research, Springer, vol. 335(2), pages 645-663, April.
  • Handle: RePEc:spr:annopr:v:335:y:2024:i:2:d:10.1007_s10479-023-05617-7
    DOI: 10.1007/s10479-023-05617-7
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    References listed on IDEAS

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    1. Silje Anderdal Bakken, 2021. "Drug dealers gone digital: using signalling theory to analyse criminal online personas and trust," Global Crime, Taylor & Francis Journals, vol. 22(1), pages 51-73, January.
    2. Freeman, Richard B., 1999. "The economics of crime," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 3, chapter 52, pages 3529-3571, Elsevier.
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    4. repec:eee:labchp:v:3:y:1999:i:pc:p:3529-3571 is not listed on IDEAS
    5. Hemant K. Bhargava & Olivier Rubel & Elizabeth J. Altman & Ramnik Arora & Jörn Boehnke & Kaitlin Daniels & Timothy Derdenger & Bryan Kirschner & Darin LaFramboise & Pantelis Loupos & Geoffrey Parker &, 2020. "Platform data strategy," Marketing Letters, Springer, vol. 31(4), pages 323-334, December.
    6. Mackey, T.K. & Kalyanam, J. & Katsuki, T. & Lanckriet, G., 2017. "Twitter-based detection of illegal online sale of prescription opioid," American Journal of Public Health, American Public Health Association, vol. 107(12), pages 1910-1915.
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