Abstract

Boko Haram has caused nearly 40,000 casualties in Nigeria, Niger, Cameroon and Chad, becoming one of the deadliest Jihadist organisations in recent history. At its current rate, Boko Haram takes part in more than two events each day, taking the lives of nearly 11 people daily. Yet, little is known concerning Boko Haram’s internal structure, organisation, and its mobility.Here, we propose a novel technique to uncover the internal structure of Boko Haram based on the sequence of events in which the terrorist group takes part. Data from the Armed Conflict Location & Event Data Project (ACLED) gives the location and time of nearly 3,800 events in which Boko Haram has been involved since the organisation became violent 10 years ago. Using this dataset, we build an algorithm to detect the fragmentation of Boko Haram into multiple cells, assuming that travel costs and reduced familiarity with unknown locations limit the mobility of individual cells.Our results suggest that the terrorist group has a very high level of fragmentation and consists of at least 50–60 separate cells. Our methodology enables us to detect periods of time during which Boko Haram exhibits exceptionally high levels of fragmentation, and identify a number of key routes frequently travelled by separate cells of Boko Haram where military interventions could be concentrated.

Highlights

  • Boko Haram is one of the deadliest armed organisations in recent history

  • Building on a comprehensive dataset that includes all violent events in northern Nigeria and the neighbouring countries since 1997, we provide an estimate of the fragmentation of Boko Haram based on an agent-based model that identifies cells which move between Boko Haram events (Epstein 2002; Moon and Carley 2007; Park et al 2012)

  • Boko Haram, a highly fragmented organisation The results of our mobility pattern analysis suggest that Boko Haram is a highly fragmented terrorist organisation

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Summary

Introduction

Boko Haram is one of the deadliest armed organisations in recent history. Since the Jihadist group became violent in 2009, it has caused nearly 40,000 casualties and displaced 2.4 million people around Lake Chad, an impoverished region divided between Nigeria, Niger, Cameroon and Chad in West Africa (UNHCR, 2019). Boko Haram is split between a faction led by Abubakar Shekau that controls parts of Borno State around Gwoza and the CameroonNigeria border, and another faction led by Abu Mus’ab al-Barnawi, that is mainly active in the islands of Lake Chad, West of Maiduguri and along the Niger border in the Diffa region (Seignobos 2017). Complex networks and quantitative models of crime and terrorism Network analysis can yield powerful insights into the latent structure of spatial and temporal data, as it is often the case with violent events (Yuan et al 2019). Despite potential “hidden” data limitations, network-based studies of crime and terrorism have rapidly expanded since the beginning of the 2000s due to the availability of new data sources and the development of complex networks and quantitative models. Social networks have been used to model the diffusion of fear of crime as a reaction to direct and indirect victimisation (Prieto Curiel and Bishop 2017), providing a potential explanation as to why fear of crime can increase even if crime rates are being reduced (Prieto Curiel and Bishop 2018)

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