Space&amp;;#x02013;Time Analysis of Point Patterns in Crime and Security Events

Johnson, SD; Marchione, Elio; Braithwaite, Alex; Davies, T.

doi:10.1002/9781118937426.ch8

Cited by 2 publications

(2 citation statements)

References 49 publications

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“…A self-exciting process is based on the idea that the rate of events λ(t) can be modelled depending on the events that have occurred up to time t. A self-exciting process is one type of extension to the Poisson model where the function λ(t) is assumed to jump after the occurrence of an event, with a subsequent cooling down process, capturing some retaliation. This model has been used to model burglaries, gang violence, and terrorist events [6,27,36,64,69,70].…”

Section: Plos Onementioning

confidence: 99%

Detecting trends and shocks in terrorist activities

Prieto-Curiel,

Walther,

Davies

2023

PLoS ONE

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Although there are some techniques for dealing with sparse and concentrated discrete data, standard time-series analyses appear ill-suited to understanding the temporal patterns of terrorist attacks due to the sparsity of the events. This article addresses these issues by proposing a novel technique for analysing low-frequency temporal events, such as terrorism, based on their cumulative curve and corresponding gradients. Using an iterative algorithm based on a piecewise linear function, our technique detects trends and shocks observed in the events associated with terrorist groups that would not necessarily be visible using other methods. The analysis leverages disaggregated data on political violence from the Armed Conflict Location & Event Data Project (ACLED) to analyse the intensity of the two most violent terrorist organisations in Africa: Boko Haram (including its splinter group, the Islamic State West Africa Province), and Al-Shabaab. Our method detects moments when terrorist groups change their capabilities to conduct daily attacks and, by taking into account the directionality of attacks, highlights major changes in the government’s strategies. Results suggest that security policies have largely failed to reduce both groups’ forces and restore stability.

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Section: Plos Onementioning

confidence: 99%

Detecting trends and shocks in terrorist activities

Prieto-Curiel,

Walther,

Davies

2023

PLoS ONE

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“…Our model (algorithm) for constructing different Boko Haram cells is based on the principle of least action which assumes that the mobility of Boko Haram is constrained by environmental (distance, lack of roads) and security factors (presence of government forces) that reduce familiarity with unknown locations and limit the impact of its attacks. Boko Haram events are analysed in sequential order in a manner similar to that used previously to detect crime pattern motifs (Davies et al 2016). Specifically, the algorithm assesses each event, assuming that cells move as little as needed.…”

Section: Datamentioning

confidence: 99%

Uncovering the internal structure of Boko Haram through its mobility patterns

2020

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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.

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Space&;#x02013;Time Analysis of Point Patterns in Crime and Security Events

Cited by 2 publications

References 49 publications

Detecting trends and shocks in terrorist activities

Detecting trends and shocks in terrorist activities

Uncovering the internal structure of Boko Haram through its mobility patterns

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