IDEAS home Printed from https://ideas.repec.org/a/spr/jcsosc/v7y2024i2d10.1007_s42001-024-00301-7.html
   My bibliography  Save this article

Estimating the command hierarchy of a drug trafficking group based on criminals’ telecommunication network

Author

Listed:
  • Yen-Sheng Chiang

    (Academia Sinica)

  • Po-Yuan Chang

    (Fu Jen Catholic University)

  • Ben-Chang Shia

    (Fu Jen Catholic University)

Abstract

It remains a puzzle whether status hierarchies, commonly found in legitimate economic organizations, also exist within organized crime groups. Wiretap data from criminal communications serves as a crucial source for tracing individual statuses within these organizations. We have transformed the telecommunications of a drug trafficking group into both static and temporal networks for analysis. Using these networks, we applied an optimization method to estimate each criminal’s position in the hierarchy. This method matches the weight and direction of each observed network tie to expected rankings, assuming higher-ranked criminals are more likely to initiate calls to subordinates rather than vice versa. The estimated hierarchy for the criminal group (n = 8) resembles a pyramid-like structure, typically three to four levels high, with fewer individuals at the top and more at the bottom. Although verification is challenging due to limited evidence, our estimates largely align with the crime details outlined in court verdicts.

Suggested Citation

  • Yen-Sheng Chiang & Po-Yuan Chang & Ben-Chang Shia, 2024. "Estimating the command hierarchy of a drug trafficking group based on criminals’ telecommunication network," Journal of Computational Social Science, Springer, vol. 7(2), pages 2107-2120, October.
    • Handle: RePEc:spr:jcsosc:v:7:y:2024:i:2:d:10.1007_s42001-024-00301-7
    DOI: 10.1007/s42001-024-00301-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s42001-024-00301-7
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s42001-024-00301-7?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Denis Bouyssou & Marchant Thierry, 2018. "The β -ranking and the β -measure for directed networks: Axiomatic characterizations," Post-Print hal-02096392, HAL.
    2. Aming Li & Lei Zhou & Qi Su & Sean P. Cornelius & Yang-Yu Liu & Long Wang & Simon A. Levin, 2020. "Evolution of cooperation on temporal networks," Nature Communications, Nature, vol. 11(1), pages 1-9, December.
    3. Olivier Mascaro & Nicolas Goupil & Hugo Pantecouteau & Adeline Depierreux & Jean-Baptiste Henst & Nicolas Claidière, 2023. "Human and animal dominance hierarchies show a pyramidal structure guiding adult and infant social inferences," Nature Human Behaviour, Nature, vol. 7(8), pages 1294-1306, August.
    4. Lucia Cavallaro & Annamaria Ficara & Pasquale De Meo & Giacomo Fiumara & Salvatore Catanese & Ovidiu Bagdasar & Wei Song & Antonio Liotta, 2020. "Disrupting resilient criminal networks through data analysis: The case of Sicilian Mafia," PLOS ONE, Public Library of Science, vol. 15(8), pages 1-22, August.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Anzhi Sheng & Qi Su & Aming Li & Long Wang & Joshua B. Plotkin, 2023. "Constructing temporal networks with bursty activity patterns," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    2. Yue Wang & Ning Li & Bin Zhang & Qian Huang & Jian Wu & Yang Wang, 2023. "The effect of structural holes on producing novel and disruptive research in physics," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(3), pages 1801-1823, March.
    3. van den Brink, René & Rusinowska, Agnieszka, 2022. "The degree measure as utility function over positions in graphs and digraphs," European Journal of Operational Research, Elsevier, vol. 299(3), pages 1033-1044.
    4. Brink, René van den & Rusinowska, Agnieszka, 2021. "The degree ratio ranking method for directed graphs," European Journal of Operational Research, Elsevier, vol. 288(2), pages 563-575.
    5. Li, Wenyao & Cai, Meng & Zhong, Xiaoni & Liu, Yanbing & Lin, Tao & Wang, Wei, 2023. "Coevolution of epidemic and infodemic on higher-order networks," Chaos, Solitons & Fractals, Elsevier, vol. 168(C).
    6. Li, Xiaopeng & Han, Weiwei & Yang, Wenjun & Wang, Juan & Xia, Chengyi & Li, Hui-jia & Shi, Yong, 2022. "Impact of resource-based conditional interaction on cooperation in spatial social dilemmas," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 594(C).
    7. Fang, Yujuan & Wei, Wei & Mei, Shengwei, 2022. "How dynamic renewable portfolio standards impact the diffusion of renewable energy in China? A networked evolutionary game analysis," Renewable Energy, Elsevier, vol. 193(C), pages 778-788.
    8. Niles Breuer & Federico Varese, 2023. "The Structure of Trade-type and Governance-type Organized Crime Groups: A Network Study," The British Journal of Criminology, Centre for Crime and Justice Studies, vol. 63(4), pages 867-888.
    9. Yang, Shulan & Hou, Zhiwei & Chen, Hongbo, 2023. "Evaluation of vulnerability of MAV/UAV collaborative combat network based on complex network," Chaos, Solitons & Fractals, Elsevier, vol. 172(C).
    10. Zeng, Ziyan & Li, Yuhan & Feng, Minyu, 2022. "The spatial inheritance enhances cooperation in weak prisoner’s dilemmas with agents’ exponential lifespan," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 593(C).
    11. Ma, Yin-Jie & Jiang, Zhi-Qiang & Podobnik, Boris, 2022. "Predictability of players’ actions as a mechanism to boost cooperation," Chaos, Solitons & Fractals, Elsevier, vol. 164(C).
    12. Juanjuan Luo & Teng Fei & Meng Tian & Yifei Liu & Meng Bian, 2023. "Sensitivity metrics of complex network based on co-occurrence truth table: exemplified by a high-speed rail network," Journal of Geographical Systems, Springer, vol. 25(4), pages 519-538, October.
    13. Li, Bin-Quan & Wu, Zhi-Xi & Guan, Jian-Yue, 2022. "Critical thresholds of benefit distribution in an extended snowdrift game model," Chaos, Solitons & Fractals, Elsevier, vol. 157(C).
    14. Cheng, Jiangjiang & Mei, Wenjun & Su, Wei & Chen, Ge, 2023. "Evolutionary games on networks: Phase transition, quasi-equilibrium, and mathematical principles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 611(C).
    15. Yuguang Yang & Katharine Z. Coyte & Kevin R. Foster & Aming Li, 2023. "Reactivity of complex communities can be more important than stability," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    16. Sebestyén, Tamás & Braun, Emese, 2022. "Hány fecske csinál nyarat? A nem teljes hálózati szerkezet és az attitűd hatása az együttműködésre [How many swallows make a summer? The impact of incomplete network structure and attitude on coope," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(7), pages 869-901.
    17. Chu, Chen & Cui, Simin & Yuan, Zheng & Yu, Chunbin, 2022. "A win-stay-lose-learn mechanism based on aspiration can promote cooperation in a multigame," Chaos, Solitons & Fractals, Elsevier, vol. 159(C).
    18. Du, Jinming & Wu, Ziren, 2023. "Coevolutionary dynamics of strategy and network structure with publicity mechanism," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 623(C).
    19. Annamaria Ficara & Giacomo Fiumara & Salvatore Catanese & Pasquale De Meo & Xiaoyang Liu, 2022. "The Whole Is Greater than the Sum of the Parts: A Multilayer Approach on Criminal Networks," Future Internet, MDPI, vol. 14(5), pages 1-21, April.
    20. Fabio Bento & Marco Tagliabue & Flora Lorenzo, 2020. "Organizational Silos: A Scoping Review Informed by a Behavioral Perspective on Systems and Networks," Societies, MDPI, vol. 10(3), pages 1-27, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:jcsosc:v:7:y:2024:i:2:d:10.1007_s42001-024-00301-7. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.