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The effect of drone strikes on civilian communication: evidence from Yemen

Published online by Cambridge University Press:  15 June 2021

Fotini Christia
Affiliation:
Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
Spyros I. Zoumpoulis
Affiliation:
INSEAD, Fontainebleau, France
Michael Freedman
Affiliation:
University of Haifa, Haifa, Israel Hebrew University of Jerusalem, Jerusalem, Israel
Leon Yao
Affiliation:
Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
Ali Jadbabaie*
Affiliation:
Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
*
*Corresponding author. Email: [email protected]

Abstract

Although covert warfare does not readily lend itself to scientific inquiry, new technologies are increasingly providing scholars with tools that enable such research. In this note, we examine the effects of drone strikes on patterns of communication in Yemen using big data and anomaly detection methods. The combination of these analytic tools allows us to not only quantify some of the effects of drone strikes, but also to compare them to other shocks. We find that on average drone strikes leave a footprint in their aftermath, spurring significant but localized spikes in communication. This suggests that drone strikes are not a purely surgical intervention, but rather have a disruptive impact on the local population.

Keywords

Type
Research Note
Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press on behalf of the European Political Science Association

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References

Bagrow, JP, Wang, D and Barabási, A-L (2011) Collective response of human populations to large-scale emergencies. PLoS ONE 6, e17680.CrossRefGoogle ScholarPubMed
Baldo, N and Closas, P (2013) Disease outbreak detection by mobile network monitoring: a case study with the D4D datasets in Proceedings of third conference on the Analysis of Mobile Phone Datasets (NetMob 2013), 1-3 May 2013, MIT, Cambridge, MA (USA).NetMob D4D Challenge 14.Google Scholar
Beath, A, Christia, F and Enikolopov, R (2013) Empowering women through development aid: evidence from a field experiment in Afghanistan. American Political Science Review 107, 540557.10.1017/S0003055413000270CrossRefGoogle Scholar
Berman, E, Felter, JH and Shapiro, JN (2018) Small Wars, Big Data: The Information Revolution in Modern Conflict. Princeton University Press. ISBN 9780691177076.Google Scholar
Bertolotti, P, Christia, F and Jadbabaie, A (2019) The social network effects of drone strikes. Working Paper.Google Scholar
Bertolotti, P, Jadbabaie, A and Christia, F (2020) Tests for network cascades via branching processes. IEEE Transactions on Network Science and Engineering 7, 26932701.10.1109/TNSE.2020.2981327CrossRefGoogle Scholar
Blair, G, Fair, CC, Malhotra, N and Shapiro, JN (2013) Poverty and support for militant politics: evidence from Pakistan. American Journal of Political Science 57, 3048.CrossRefGoogle Scholar
Blair, G, Imai, K and Lyall, J (2014) Comparing and combining list and endorsement experiments: evidence from Afghanistan. American Journal of Political Science 58, 10431063.10.1111/ajps.12086CrossRefGoogle Scholar
Blumenstock, JE (2012) Inferring patterns of internal migration from mobile phone call records: evidence from Rwanda. Information Technology for Development 18, 107125.10.1080/02681102.2011.643209CrossRefGoogle Scholar
Blumenstock, JE (2016) Fighting poverty with data. Science 353, 753754.10.1126/science.aah5217CrossRefGoogle ScholarPubMed
Blumenstock, JE and Eagle, N (2012) Divided we call: disparities in access and use of mobile phones in Rwanda. Information Technologies and International Development 8, 116.Google Scholar
Boyle, MJ (2013) The costs and consequences of drone warfare. International Affairs 89, 129.10.1111/1468-2346.12002CrossRefGoogle Scholar
Bozcaga, T, Christia, F, Daskalakis, C, Harwood, E and Papadimitriou, C (2019) Assessing Syrian refugee integration using call detail records from Turkey. In Salah, AA, Pentland, A, Lepri, B and Letouzé, E (eds). Guide to Mobile Data Analytics in Refugee Scenarios. Springer, pp. 223249. ISBN 978-3-030-12554-7.CrossRefGoogle Scholar
Candia, J, González, MC, Wang, P, Schoenharl, T, Madey, G and Barabási, A-L (2008) Uncovering individual and collective human dynamics from mobile phone records. Journal of Physics A: Mathematical and Theoretical 41, 224015.10.1088/1751-8113/41/22/224015CrossRefGoogle Scholar
Dafoe, A and Lyall, J (2015) From cell phones to conflict? Reflections on the emerging ICT-political conflict research agenda. Journal of Peace Research 52, 401413.10.1177/0022343314563653CrossRefGoogle Scholar
Eagle, N, Pentland, ASS and Lazer, D (2009) Inferring friendship network structure by using mobile phone data. Proceedings of the National Academy of Sciences 106, 1527415278.10.1073/pnas.0900282106CrossRefGoogle ScholarPubMed
Gelvanovska, N, Rogy, M and Rossotto, CM (2014) Broadband Networks in the Middle East and North Africa: Accelerating High-Speed Internet Access. Directions in Development–Communication and Information Technologies, Washington, DC: The World Bank. © World Bank. https://openknowledge.worldbank.org/handle/10986/16680. License: CC BY 3.0 IGO.Google Scholar
Gonzalez, MC, Hidalgo, CA and Barabasi, A-L (2008) Understanding individual human mobility patterns. Nature 453, 779782.10.1038/nature06958CrossRefGoogle ScholarPubMed
Hazelton, JL (2017) Drone strikes and grand strategy: toward a political understanding of the uses of unmanned aerial vehicle attacks in US security policy. Journal of Strategic Studies 40, 6891.10.1080/01402390.2016.1196589CrossRefGoogle Scholar
Horowitz, MC, Kreps, SE and Fuhrmann, M (2016) Separating fact from fiction in the debate over drone proliferation. International Security 41, 742.10.1162/ISEC_a_00257CrossRefGoogle Scholar
Hudson, L, Owens, CS and Callen, DJ (2012) Drone warfare in Yemen: fostering emirates through counterterrorism?. Middle East Policy 19, 142156.10.1111/j.1475-4967.2012.00554.xCrossRefGoogle Scholar
Johnston, PB (2012) Does decapitation work? Assessing the effectiveness of leadership targeting in counterinsurgency campaigns. International Security 36, 4779.CrossRefGoogle Scholar
Johnston, PB, Sarbahi, AK, Dylan, B-L, Gabriel, K-D, Don, R and Muhammad, AU (2016) The impact of US drone strikes on terrorism in Pakistan. International Studies Quarterly 60, 203219.10.1093/isq/sqv004CrossRefGoogle Scholar
Jordan, J (2014) The effectiveness of the drone campaign against Al Qaeda central: a case study. Journal of Strategic Studies 37, 429.CrossRefGoogle Scholar
Lazer, D, Kennedy, R, King, G and Vespignani, A (2014) The parable of Google flu: traps in big data analysis. Science 343, 12031205.CrossRefGoogle ScholarPubMed
Lima, A, De Domenico, M, Pejovic, V and Musolesi, M (2015) Disease containment strategies based on mobility and information dissemination. Scientific Reports 5, 10650.10.1038/srep10650CrossRefGoogle ScholarPubMed
Mari, L, Gatto, M, Ciddio, M, Dia, ED, Sokolow, SH, De Leo, GA and Casagrandi, R (2017) Big-data-driven modeling unveils country-wide drivers of endemic schistosomiasis. Scientific Reports 7, 489.CrossRefGoogle ScholarPubMed
Mir, A (2018) What explains counterterrorism effectiveness? Evidence from the U.S. drone war in Pakistan. International Security 43, 4583.10.1162/isec_a_00331CrossRefGoogle Scholar
Mir, A and Moore, D (2019) Drones, surveillance, and violence: theory and evidence from a US drone program. International Studies Quarterly 63, 846862.Google Scholar
Papadogeorgou, G, Imai, K, Lyall, J and Li, F (2020) Causal inference with spatio-temporal data: estimating the effects of airstrikes on insurgent violence in Iraq. arXiv preprint arXiv:2003.13555.Google Scholar
Price, BC (2012) Targeting top terrorists: how leadership decapitation contributes to counterterrorism. International Security 36, 946.10.1162/ISEC_a_00075CrossRefGoogle Scholar
Shah, A (2018) Do US drone strikes cause blowback? Evidence from Pakistan and beyond. International Security 42, 4784.10.1162/isec_a_00312CrossRefGoogle Scholar
Shapiro, JN and Weidmann, NB (2015) Is the phone mightier than the sword? Cellphones and insurgent violence in Iraq. International Organization 69, 247274.10.1017/S0020818314000423CrossRefGoogle Scholar
Tomaszewski, B (2014) Geographic information systems (GIS) for disaster management. New York: Routledge.CrossRefGoogle Scholar
Tompkins, AM and McCreesh, N (2016) Migration statistics relevant for malaria transmission in Senegal derived from mobile phone data and used in an agent-based migration model. Geospatial Health 11 ((Supp. 1), 408.10.4081/gh.2016.408CrossRefGoogle Scholar
Wang, Y, Li, J, Zhao, X, Feng, G and Luo, XR (2020) Using mobile phone data for emergency management: a systematic literature review. Information Systems Frontiers, 121. doi:10.1007/s10796-020-10057-w.Google ScholarPubMed
Weidmann, NB (2015) Communication, technology, and political conflict. Journal of Peace Research 52, 263268.10.1177/0022343314559081CrossRefGoogle Scholar
Williams, BG (2013) Predators: The CIA's Drone War on al Qaeda. Potomac Books, Inc.10.2307/j.ctt1ddr6sfCrossRefGoogle Scholar
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