Fluctuation Scaling, Taylor’s Law, and Crime

Hanley, QS ORCID: https://orcid.org/0000-0002-8189-9550, Khatun, S, Yosef, A and Dyer, R-M, 2014. Fluctuation Scaling, Taylor’s Law, and Crime. PLoS ONE, 9 (10), e109004. ISSN 1932-6203

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Abstract

Fluctuation scaling relationships have been observed in a wide range of processes ranging from internet router traffic to measles cases. Taylor’s law is one such scaling relationship and has been widely applied in ecology to understand communities including trees, birds, human populations, and insects. We show that monthly crime reports in the UK show complex fluctuation scaling which can be approximated by Taylor’s law relationships corresponding to local policing neighborhoods and larger regional and countrywide scales. Regression models applied to local scale data from Derbyshire and Nottinghamshire found that different categories of crime exhibited different scaling exponents with no significant difference between the two regions. On this scale, violence reports were close to a Poisson distribution (α = 1.057±0.026) while burglary exhibited a greater exponent (α = 1.292±0.029) indicative of temporal clustering. These two regions exhibited significantly different pre-exponential factors for the categories of anti-social behavior and burglary indicating that local variations in crime reports can be assessed using fluctuation scaling methods. At regional and countrywide scales, all categories exhibited scaling behavior indicative of temporal clustering evidenced by Taylor’s law exponents from 1.43±0.12 (Drugs) to 2.094±0081 (Other Crimes). Investigating crime behavior via fluctuation scaling gives insight beyond that of raw numbers and is unique in reporting on all processes contributing to the observed variance and is either robust to or exhibits signs of many types of data manipulation.

Item Type:	Journal article
Publication Title:	PLoS ONE
Creators:	Hanley, Q.S., Khatun, S., Yosef, A. and Dyer, R.-M.
Publisher:	Public Library of Science
Date:	2014
Volume:	9
Number:	10
ISSN:	1932-6203
Identifiers:	Number Type 10.1371/journal.pone.0109004 DOI
Divisions:	Schools > School of Science and Technology
Record created by:	Jonathan Gallacher
Date Added:	25 Feb 2016 09:27
Last Modified:	09 Jun 2017 13:59
URI:	https://irep.ntu.ac.uk/id/eprint/27034

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