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Spatio-temporal patterns of IED usage by the Provisional Irish Republican Army

Published online by Cambridge University Press:  20 January 2016

STEPHEN TENCH
Affiliation:
UCL Jill Dando Institute of Security and Crime Science, 35 Tavistock Square, WC1H 9EZ, London, UK email: [email protected], [email protected] UCL Centre for Advanced Spatial Analysis, 90 Tottenham Court Road, W1T 4TJ, London, UK email: [email protected]
HANNAH FRY
Affiliation:
UCL Centre for Advanced Spatial Analysis, 90 Tottenham Court Road, W1T 4TJ, London, UK email: [email protected]
PAUL GILL
Affiliation:
UCL Jill Dando Institute of Security and Crime Science, 35 Tavistock Square, WC1H 9EZ, London, UK email: [email protected], [email protected]

Abstract

In this paper, a unique dataset of improvised explosive device attacks during “The Troubles” in Northern Ireland (NI) is analysed via a Hawkes process model. It is found that this past dependent model is a good fit to improvised explosive device attacks yielding key insights about the nature of terrorism in NI. We also present a novel approach to quantitatively investigate some of the sociological theory surrounding the Provisional Irish Republican Army which challenges previously held assumptions concerning changes seen in the organisation. Finally, we extend our use of the Hawkes process model by considering a multidimensional version which permits both self and mutual-excitations. This allows us to test how the Provisional Irish Republican Army responded to past improvised explosive device attacks on different geographical scales from which we find evidence for the autonomy of the organisation over the six counties of NI and Belfast. By incorporating a second dataset concerning British Security Force (BSF) interventions, the multidimensional model allows us to test counter-terrorism (CT) operations in NI where we find subsequent increases in violence.

Type
Papers
Copyright
Copyright © Cambridge University Press 2016 

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References

[1]Akaike, H. (1974–12) A new look at the statistical model identification. IEEE T. Automat. Contr. 19 (6), 716723.CrossRefGoogle Scholar
[2]Andresen, M. A. & Malleson, N. (2011) Testing the stability of crime patterns: Implications for theory and policy. J. Res. Crime Delinq. 48 (1), 5882.Google Scholar
[3]Asal, V., Gill, P., Rethemeyer, R. K. & Horgan, J. (2013) Killing range: Explaining lethality variance within a terrorist organization. J. Conict Resolut. 59 (3), 401427. http://jcr.sagepub.com/content/early/2014/04/24/0022002713508927Google Scholar
[4]Berman, M. (1983) Comment on “Likelihood analysis of point processes and its applications to seismological data”, by Y. Ogata. Bull. Int. Stat. Inst. 50 (3), 412418.Google Scholar
[5]Bowsher, C. G. (2007–12) Modelling security market events in continuous time: Intensity based, multivariate point process models. J. Econometrics 141 (2), 876912. http://www.sciencedirect.com/science/article/pii/S030440760600251XGoogle Scholar
[6]Braga, A. A. (2001-11-01) The effects of hot spots policing on crime. Ann. Am. Acad. Polit. Ss. 578 (1), 104125. http://ann.sagepub.com/content/578/1/104Google Scholar
[7]Braithwaite, A. & Johnson, S. D. (2012-03-01) Space-time modeling of insurgency and counterinsurgency in Iraq. J. Quant. Criminol. 28 (1), 3148. http://link.springer.com/article/10.1007/s10940-011-9152-8Google Scholar
[8]Brantingham, P. J. & Brantingham, P. L. (1984) Patterns in Crime, New York: Macmillan.Google Scholar
[9]Brémaud, P. & Massoulié, L. (1996-07-01) Stability of nonlinear hawkes processes. Ann. Probab. 24 (3), 15631588. http://www.jstor.org/stable/2244985Google Scholar
[10]Brown, E. N., Barbieri, R., Ventura, V., Kass, R. E. & Frank, L. M. (2002-02) The time-rescaling theorem and its application to neural spike train data analysis. Neural Comput. 14 (2), 325–346. http://www.mitpressjournals.org/doi/pdfplus/10.1162/08997660252741149CrossRefGoogle ScholarPubMed
[11]Burnham, K. P. & Anderson, D. R. (2002-07-12) Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach, 2nd ed., New York: Springer Science & Business Media.Google Scholar
[12]Campbell, C. & Connolly, I. (2003) A model for the “War Against Terrorism”? Military intervention in northern Ireland and the 1970 falls curfew. J. Law Soc. 30 (3), 341375.Google Scholar
[13]Chen, Z., Purdon, P., Brown, E. N. & Barbieri, R. (2012) A unified point process probabilistic framework to assess heartbeat dynamics and autonomic cardiovascular control. Front. Physio. 3 (4), 114. http://journal.frontiersin.org/Journal/10.3389/fphys.2012.00004/fullGoogle Scholar
[14]Clauset, A. & Woodard, R. (2013) Estimating the historical and future probabilities of large terrorist events. J. Appl. Stat. 7 (4), 18381865.Google Scholar
[15]Coogan, T. P. (2002) The IRA, New York: Palgrave.Google Scholar
[16]Eck, J. E., Chainey, S., Cameron, J. G., Leitner, M. & Wilson, R. E. (2005) Mapping Crime: Understanding Hot Spots, Washington: U.S. Department of Justice. http://discovery.ucl.ac.uk/11291/1/11291.pdfGoogle Scholar
[17]Eck, J. E. & Weisburd, D. (1995) Crime Prevention Series, Volume 4: Crime and Place, New York: Criminal Justice Press.Google Scholar
[18]Egesdal, M., Fathauer, C., Louie, K. & Neuman, J. (2010) Statistical and stochastic modeling of gang rivalries in los angeles. SIURO 3, 7294.CrossRefGoogle Scholar
[19]English, R. (2004) Armed Struggle: The History of the IRA, London: Pan Macmillan.Google Scholar
[20]Fay, M.-T., Morrissey, M. & Smyth, M. (1999) Northern Ireland's Troubles: The Human Costs, London: Pluto Press.Google Scholar
[21]Fox, E. W., Short, M. B., Schoenberg, F. P., Coronges, K. D. & Bertozzi, A. L. (2014) Modeling e-mail networks and inferring leadership using self-exciting point processes'. http://people.math.gatech.edu/~mshort9/papers/IkeNet.pdf [Accessed: 11/1/2016].Google Scholar
[22]Gao, P., Guo, D., Liao, K., Webb, J. J. & Cutter, S. L. (2013) Early detection of terrorism outbreaks using prospective space-time scan statistics. Prof. Geogr. 65 (4), 676691.Google Scholar
[23]Hawkes, A. G. (1971-04-01) Spectra of some self-exciting and mutually exciting point processes. Biometrika 58 (1), 8390. http://www.jstor.org/stable/2334319Google Scholar
[24]Hegemann, R. A., Lewis, E. A. & Bertozzi, A. L. (2013) An “estimate & score algorithm” for simultaneous parameter estimation and reconstruction of incomplete data on social networks. Secur. Inform. 2 (1), 113.CrossRefGoogle Scholar
[25]Horgan, J. & Taylor, M. (1997) The provisional irish republican army: Command and functional structure. Terror Polit. Violenc. 9 (3), 132. http://dx.doi.org/10.1080/09546559708427413CrossRefGoogle Scholar
[26]Johnson, N. F., Medina, P., Zhao, G., Messinger, D. S., Horgan, J., Gill, P., Bohorquez, J. C., Mattson, W., Gangi, D., Qi, H., Manrique, P., Velasquez, N., Morgenstern, A., Restrepo, E., Johnson, N., Spagat, M. & Zarama, R. (2013) Simple mathematical law benchmarks human confrontations. Sci. Rep. 3, 16. http://www.nature.com/srep/2013/131210/srep03463/full/srep03463.htmlGoogle Scholar
[27]Johnson, S. D. & Bowers, K. J. (2004-04-01) The burglary as clue to the future the beginnings of prospective hot-spotting. Eur. J. Criminol. 1 (2), 237255. http://euc.sagepub.com/content/1/2/237CrossRefGoogle Scholar
[28]Lafree, G., Dugan, L. & Korte, R. (2009-02) The impact of british counterterrorist strategies on political violence in northern ireland: Comparing deterrence and backlash models. Criminology 47 (1), 1745. http://onlinelibrary.wiley.com/doi/10.1111/j.1745-9125.2009.00138.x/abstractCrossRefGoogle Scholar
[29]Lewis, E., Mohler, G., Brantingham, P. J. & Bertozzi, A. L. (2012-07) Self-exciting point process models of civilian deaths in iraq. Secur. J. 25 (3), 244264. http://www.palgrave-journals.com/sj/journal/v25/n3/abs/sj201121a.htmlCrossRefGoogle Scholar
[30]Liniger, T. (2009) Multivariate Hawkes processes. PhD thesis. Zurich: Swiss Federal Institute of Technology. http://e-collection.library.ethz.ch/eserv/eth:1112/eth-1112-02.pdf?pid=eth:1112&dsID=eth-1112-02.pdfGoogle Scholar
[31]Lum, C. & Kennedy, L. W. (2012) Evidence-Based Counterterrorism Policy, New York: Springer Science + Business Media.CrossRefGoogle Scholar
[32]Massey, F. J. Jr., (1951-03-01) The kolmogorov-smirnov test for goodness of fit. J. Am. Stat. Assoc. 46 (253), 6878. http://www.jstor.org/stable/2280095Google Scholar
[33]Memon, N., Farley, J. D., Hicks, D. L. & Rosenorn, T. (2009-08) Mathematical Methods in Counterterrorism, New York: Springer Science + Business Media.Google Scholar
[34]Mohler, G. (2013-09) Modeling and estimation of multi-source clustering in crime and security data. Ann. Appl. Stat. 7 (3), 15251539. http://projecteuclid.org/euclid.aoas/1380804805Google Scholar
[35]Mohler, G. O., Short, M. B., Brantingham, P. J., Schoenberg, F. P. & Tita, G. E. (2011) Self-exciting point process modeling of crime. J. Am. Stat. Assoc. 106 (493), 100108.Google Scholar
[36]Moloney, E. (2003) A Secret History of the IRA, New York: W. W. Norton.Google Scholar
[37]Nelder, J. A. & Mead, R. (1965-01-01) A simplex method for function minimization. Comput. J. 7 (4), 308313. http://comjnl.oxfordjournals.org/content/7/4/308Google Scholar
[38]Nichols, K. & Schoenberg, F. P. (2014-05-01) Assessing the dependency between the magnitudes of earthquakes and the magnitudes of their aftershocks. Environmetrics 25 (3), 143151. http://onlinelibrary.wiley.com/doi/10.1002/env.2268/abstractGoogle Scholar
[39]O'Brien, B. (1999) The Long War: The IRA and Sinn Féin, 2nd ed., New York: Syracuse University Press.Google Scholar
[40]O'Connor, M. P. & Rumann, C. (2003) Into the fire: How to avoid getting burned by the same mistakes made fighting terrorism in northern ireland. Cardozo Law Rev. 24 (4), 16571751.Google Scholar
[41]O'Connor, P. D. T. & Kleyner, A. (2012) Practical Reliability Engineering, 5th ed., West Sussex: Wiley.Google Scholar
[42]Ozaki, T. (1979-12-01) Maximum likelihood estimation of hawkes' self-exciting point processes. Ann. I. Stat. Math. 31 (1), 145155. http://link.springer.com/article/10.1007/BF02480272CrossRefGoogle Scholar
[43]Papangelou, F. (1972-03-01) Integrability of expected increments of point processes and a related random change of scale. T. Am. Math. Soc. 165, 483506. http://www.jstor.org/stable/1995899Google Scholar
[44]Pease, K. (1998) Repeat Victimisation: Taking Stock, London: Home Office Police Research Group. http://www.popcenter.org/problems/domestic_violence/PDFs/Pease_1998.pdfGoogle Scholar
[45]Peng, R. (2003-09) Multi-dimensional point process models in R. J. Stat. Softw. 8 (16), 127.Google Scholar
[46]Rasmussen, J. G. (2013-09-01) Bayesian inference for hawkes processes. Methodol. Comput. Appl. 15 (3), 623642. http://link.springer.com/article/10.1007/s11009-011-9272-5Google Scholar
[47]Ross, S. (2010) A First Course in Probability, 8th ed., London: Pearson.Google Scholar
[48]Rubin, I. (1972) Regular point processes and their detection. IEEE T. Inform. Theory IT–18 (5), 547557.Google Scholar
[50]Short, M. B., Mohler, G. O., Brantingham, P. J. & Tita, G. E. (2014) Gang rivalry dynamics via coupled point process networks. Discrete Cont. Dyn.-B 19 (5), 14591477. http://www.aimsciences.org/journals/displayArticlesnew.jsp?paperID=9866Google Scholar
[51]Stevenson, R. & Crossley, N. (2014) Change in covert social movement networks: The “inner circle'' of the provisional Irish Republican Army. Social Movement Studies 13 (1), 7091.Google Scholar
[52]Stomakhin, A., Short, M. B. & Bertozzi, A. L. (2011) Reconstruction of missing data in social networks based on temporal patterns of interactions. Inverse Probl. 27 (11), 115.Google Scholar
[53]Sutton, M. (1994) An Index of Deaths from the Conflict in Ireland 1969–1993, Belfast: Beyond the Pale.Google Scholar
[54]Varadhan, S. R. S. (2007) Stochastic Processes (Courant Lecture Notes), Rhode Island: American Mathematical Soc.Google Scholar
[55]White, G., Porter, M. D. & Mazerolle, L. (2012) Terrorism risk, resilience and volatility: A comparison of terrorism patterns in three southeast asian countries. J. Quant. Criminol. 29 (2), 295320.Google Scholar
[56]White, R. W. (1993) Provisional Irish Republicans: An Oral and Interpretive History, Westport, CT: Greenwood Press.Google Scholar
[57]Zar, J. H. (2014) Biostatistical Analysis, 5th ed., Essex: Pearson Education Limited.Google Scholar