Prediction based on time-series of aggressive behaviors. A case study Bogotá, Colombia

Victorino, Jorge; Barrero, Miguel; Rudas, Jorge; Pulido, Cristian; Chaparro, Luisa Fernanda; Estrada, Camilo; Narvaez, Luz Angela; Gómez, Francisco

doi:10.1109/iseeie55684.2022.00027

Cited by 1 publication

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“…This work also provides similar spatial estimations of underreporting but accounts for the temporal dimension, providing spatiotemporal estimates of the “true” crime incidences. Previous work on crime prediction also considers a time-based crime characterization but does not account for the underreporting phenomena [ 1 , 43 , 44 ]. In a recent paper, Brunton-Smith et al [ 21 ] have pointed out an oversimplifying assumption conventionally used for estimating the underreporting of crime events: the undercounting of events being independent of any other area characteristics or uniform across geographic scales.…”

Section: Discussionmentioning

confidence: 99%

“…This work also provides similar spatial estimations of underreporting but accounts for the temporal dimension, providing spatiotemporal estimates of the "true" crime incidences. Previous work on crime prediction also considers a time-based crime characterization but does not account for the underreporting phenomena [1,43,44]. In a recent paper, Brunton-Smith et al [21] have pointed out an…”

Section: Discussionmentioning

confidence: 99%

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Modelling underreported spatio-temporal crime events

Riascos

Ñungo

Tobón³

et al. 2023

PLoS ONE

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Crime observations are one of the principal inputs used by governments for designing citizens’ security strategies. However, crime measurements are obscured by underreporting biases, resulting in the so-called “dark figure of crime”. This work studies the possibility of recovering “true” crime and underreported incident rates over time using sequentially available daily data. For this, a novel underreporting model of spatiotemporal events based on the combinatorial multi-armed bandit framework was proposed. Through extensive simulations, the proposed methodology was validated for identifying the fundamental parameters of the proposed model: the “true” rates of incidence and underreporting of events. Once the proposed model was validated, crime data from a large city, Bogotá (Colombia), was used to estimate the “true” crime and underreporting rates. Our results suggest that this methodology could be used to rapidly estimate the underreporting rates of spatiotemporal events, which is a critical problem in public policy design.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%