IDEAS home Printed from https://ideas.repec.org/a/spr/comaot/v29y2023i3d10.1007_s10588-022-09364-1.html
   My bibliography  Save this article

Drone strikes and radicalization: an exploration utilizing agent-based modeling and data applied to Pakistan

Author

Listed:
  • Brandon Shapiro

    (George Mason University)

  • Andrew Crooks

    (University at Buffalo)

Abstract

The employment of drone strikes has been ongoing and the public continues to debate their perceived benefits. A question that persists is whether drone strikes contribute to an increase in radicalization. This paper presents a data-driven approach to explore the relationship between drone strikes conducted in Pakistan and subsequent responses, often in the form of terrorist attacks carried out by those in the communities targeted by these particular counterterrorism measures. Our exploration and analysis of news reports which discussed drone strikes and radicalization suggest that government-sanctioned drone strikes in Pakistan appear to drive terrorist events with a distributed lag that can be determined analytically. We leverage news reports to inform and calibrate an agent-based model grounded in radicalization and opinion dynamics theory. This enabled us to simulate terrorist attacks that approximated the rate and magnitude observed in Pakistan from 2007 through 2018. We argue that this research effort advances the field of radicalization and lays the foundation for further work in the area of data-driven modeling and drone strikes.

Suggested Citation

  • Brandon Shapiro & Andrew Crooks, 2023. "Drone strikes and radicalization: an exploration utilizing agent-based modeling and data applied to Pakistan," Computational and Mathematical Organization Theory, Springer, vol. 29(3), pages 415-433, September.
    • Handle: RePEc:spr:comaot:v:29:y:2023:i:3:d:10.1007_s10588-022-09364-1
    DOI: 10.1007/s10588-022-09364-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10588-022-09364-1
    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/s10588-022-09364-1?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. Mahmood, Rafat & Jetter, Michael, 2019. "Military Intervention via Drone Strikes," IZA Discussion Papers 12318, Institute of Labor Economics (IZA).
    2. F. LeRon Shults & Ross Gore & Wesley Wildman & Christopher Lynch & Justin E. Lane & Monica Toft, 2018. "A Generative Model of the Mutual Escalation of Anxiety Between Religious Groups," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 21(4), pages 1-7.
    3. Caiani, Alessandro & Godin, Antoine & Caverzasi, Eugenio & Gallegati, Mauro & Kinsella, Stephen & Stiglitz, Joseph E., 2016. "Agent based-stock flow consistent macroeconomics: Towards a benchmark model," Journal of Economic Dynamics and Control, Elsevier, vol. 69(C), pages 375-408.
    4. Serge Galam & Marco Alberto Javarone, 2016. "Modeling Radicalization Phenomena in Heterogeneous Populations," PLOS ONE, Public Library of Science, vol. 11(5), pages 1-15, May.
    5. Javier Arroyo & Samer Hassan & Celia Gutiérrez & Juan Pavón, 2010. "Re-thinking simulation: a methodological approach for the application of data mining in agent-based modelling," Computational and Mathematical Organization Theory, Springer, vol. 16(4), pages 416-435, December.
    6. Jürgen Pfeffer & Kathleen M. Carley, 2012. "Rapid modeling and analyzing networks extracted from pre-structured news articles," Computational and Mathematical Organization Theory, Springer, vol. 18(3), pages 280-299, September.
    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. Patrick Mellacher, 2021. "Growth, Inequality and Declining Business Dynamism in a Unified Schumpeter Mark I + II Model," Papers 2111.09407, arXiv.org, revised Nov 2023.
    2. Lamperti, Francesco & Bosetti, Valentina & Roventini, Andrea & Tavoni, Massimo & Treibich, Tania, 2021. "Three green financial policies to address climate risks," Journal of Financial Stability, Elsevier, vol. 54(C).
    3. Boris Podobnik & Marko Jusup & Dejan Kovac & H. E. Stanley, 2017. "Predicting the Rise of EU Right-Wing Populism in Response to Unbalanced Immigration," Complexity, Hindawi, vol. 2017, pages 1-12, August.
    4. Georg Feigl & Markus Marterbauer & Miriam Rehm & Matthias Schnetzer & Sepp Zuckerstätter & Lars Nørvang Andersen & Thea Nissen & Signe Dahl & Peter Hohlfeld & Benjamin Lojak & Achim Truger & Andrew Wa, 2016. "The Elusive Recovery," SciencePo Working papers Main hal-03459084, HAL.
      • Georg Feigl & Markus Marterbauer & Miriam Rehm & Matthias Schnetzer & Sepp Zuckerstätter & Lars Nørvang Andersen & Thea Nissen & Signe Dahl & Peter Hohlfeld & Benjamin Lojak & Achim Truger & Andrew Wa, 2016. "The Elusive Recovery," PSE-Ecole d'économie de Paris (Postprint) hal-03459084, HAL.
      • Georg Feigl & Markus Marterbauer & Miriam Rehm & Matthias Schnetzer & Sepp Zuckerstätter & Lars Nørvang Andersen & Thea Nissen & Signe Dahl & Peter Hohlfeld & Benjamin Lojak & Thomas Theobald & Achim , 2016. "The Elusive Recovery," PSE Working Papers hal-03612850, HAL.
      • Georg Feigl & Markus Marterbauer & Miriam Rehm & Matthias Schnetzer & Sepp Zuckerstätter & Lars Nørvang Andersen & Thea Nissen & Signe Dahl & Peter Hohlfeld & Benjamin Lojak & Achim Truger & Andrew Wa, 2016. "The Elusive Recovery," Post-Print hal-03459084, HAL.
      • Georg Feigl & Markus Marterbauer & Miriam Rehm & Matthias Schnetzer & Sepp Zuckerstätter & Lars Nørvang Andersen & Thea Nissen & Signe Dahl & Peter Hohlfeld & Benjamin Lojak & Thomas Theobald & Achim , 2016. "The Elusive Recovery," Working Papers hal-03612850, HAL.
      • Georg Feigl & Markus Marterbauer & Miriam Rehm & Matthias Schnetzer & Sepp Zuckerstätter & Lars Nørvang Andersen & Thea Nissen & Signe Dahl & Peter Hohlfeld & Benjamin Lojak & Thomas Theobald & Achim , 2016. "The Elusive Recovery," SciencePo Working papers Main hal-03612850, HAL.
      • Georg Feigl & Markus Marterbauer & Miriam Rehm & Matthias Schnetzer & Sepp Zuckerstätter & Lars Nørvang Andersen & Thea Nissen & Signe Dahl & Peter Hohlfeld & Benjamin Lojak & Thomas Theobald & Achim , 2016. "The Elusive Recovery," PSE-Ecole d'économie de Paris (Postprint) hal-03612850, HAL.
    5. Roberto Veneziani & Luca Zamparelli & Michalis Nikiforos & Gennaro Zezza, 2017. "Stock-Flow Consistent Macroeconomic Models: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 31(5), pages 1204-1239, December.
    6. Bell, William Paul & Zheng, Xuemei, 2018. "Inclusive growth and climate change adaptation and mitigation in Australia and China : Removing barriers to solving wicked problems," MPRA Paper 84509, University Library of Munich, Germany.
    7. repec:spo:wpmain:info:hdl:2441/50jd34uldo9jioklc7b0dpu4ej is not listed on IDEAS
    8. Canelli, Rosa & Fontana, Giuseppe & Realfonzo, Riccardo & Passarella, Marco Veronese, 2024. "Energy crisis, economic growth and public finance in Italy," Energy Economics, Elsevier, vol. 132(C).
    9. Crokidakis, Nuno & Sigaud, Lucas, 2021. "Modeling the evolution of drinking behavior: A Statistical Physics perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 570(C).
    10. Fierro, Luca Eduardo & Giri, Federico & Russo, Alberto, 2023. "Inequality-constrained monetary policy in a financialized economy," Journal of Economic Behavior & Organization, Elsevier, vol. 216(C), pages 366-385.
    11. Pascal Seppecher & Isabelle Salle & Dany Lang, 2019. "Is the market really a good teacher?," Journal of Evolutionary Economics, Springer, vol. 29(1), pages 299-335, March.
    12. Barde, Sylvain, 2020. "Macroeconomic simulation comparison with a multivariate extension of the Markov information criterion," Journal of Economic Dynamics and Control, Elsevier, vol. 111(C).
    13. Tommaso Ciarli & André Lorentz & Marco Valente & Maria Savona, 2019. "Structural changes and growth regimes," Journal of Evolutionary Economics, Springer, vol. 29(1), pages 119-176, March.
    14. Lamperti, Francesco & Roventini, Andrea & Sani, Amir, 2018. "Agent-based model calibration using machine learning surrogates," Journal of Economic Dynamics and Control, Elsevier, vol. 90(C), pages 366-389.
    15. Giovanni Dosi & Andrea Roventini, 2017. "Agent-Based Macroeconomics and Classical Political Economy: Some Italian Roots," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 3(3), pages 261-283, November.
    16. Claudius Graebner & Jakob Kapeller, 2015. "The Micro-Macro Link in Heterodox Economics," ICAE Working Papers 37, Johannes Kepler University, Institute for Comprehensive Analysis of the Economy.
    17. Ramis Khabibullin & Alexey Ponomarenko & Sergei Seleznev, 2018. "Forecasting the implications of foreign exchange reserve accumulation with an agent-based model," Bank of Russia Working Paper Series wps37, Bank of Russia.
    18. Domenico Delli Gatti & Severin Reissl & Enrico Turco, 2023. "V for vaccines and variants," Journal of Evolutionary Economics, Springer, vol. 33(4), pages 991-1046, September.
    19. Barde, Sylvain, 2024. "Bayesian estimation of large-scale simulation models with Gaussian process regression surrogates," Computational Statistics & Data Analysis, Elsevier, vol. 196(C).
    20. Otto, Christian & Willner, Sven Norman & Wenz, Leonie & Frieler, Katja & Levermann, Anders, 2017. "Modeling loss-propagation in the global supply network: The dynamic agent-based model acclimate," OSF Preprints 7yyhd, Center for Open Science.
    21. Siyan Chen & Saul Desiderio, 2023. "An agent-based framework for the analysis of the macroeconomic effects of population aging," Journal of Evolutionary Economics, Springer, vol. 33(2), pages 393-427, April.

    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:comaot:v:29:y:2023:i:3:d:10.1007_s10588-022-09364-1. 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.