Analyzing an Offender's Journey to Crime: A Criminal Movement Model (CriMM)

Iwanski, Natalia; Frank, Richard; Dabbaghian, Vahid; Reid, Andrew A.; Brantingham, Patricia L.

doi:10.1109/eisic.2011.13

Cited by 19 publications

(22 citation statements)

References 18 publications

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“…The work in [8] investigates 10 cities in five countries and finds that the risk of residential burglary is temporarily increased for at least two weeks within a 200-m radius around burgled residences. Research into criminal behavior involves using journey-to-crime theory to suggest how burglars are likely to identify target houses prior to offending [9,10]. As such, targets are more likely to be located close to an area familiar to the offender.…”

Section: Related Workmentioning

confidence: 99%

Evaluating Temporal Analysis Methods Using Residential Burglary Data

Boldt

Borg

2016

IJGI

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Law enforcement agencies, as well as researchers rely on temporal analysis methods in many crime analyses, e.g., spatio-temporal analyses. A number of temporal analysis methods are being used, but a structured comparison in different configurations is yet to be done. This study aims to fill this research gap by comparing the accuracy of five existing, and one novel, temporal analysis methods in approximating offense times for residential burglaries that often lack precise time information. The temporal analysis methods are evaluated in eight different configurations with varying temporal resolution, as well as the amount of data (number of crimes) available during analysis. A dataset of all Swedish residential burglaries reported between 2010 and 2014 is used (N = 103,029). From that dataset, a subset of burglaries with known precise offense times is used for evaluation. The accuracy of the temporal analysis methods in approximating the distribution of burglaries with known precise offense times is investigated. The aoristic and the novel aoristic ext method perform significantly better than three of the traditional methods. Experiments show that the novel aoristic ext method was most suitable for estimating crime frequencies in the day-of-the-year temporal resolution when reduced numbers of crimes were available during analysis. In the other configurations investigated, the aoristic method showed the best results. The results also show the potential from temporal analysis methods in approximating the temporal distributions of residential burglaries in situations when limited data are available.

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Section: Related Workmentioning

confidence: 99%

Evaluating Temporal Analysis Methods Using Residential Burglary Data

Boldt

Borg

2016

IJGI

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“…Recently, crime pattern analysis that utilizes social network information has received some attention [7] [8]. Combining the crime pattern theory that was established by the Brantinghams [9], lately SNA has become an important tool for criminologists seeking to understand the connections between patterns of interactions and criminal behaviors.…”

Section: A Social Network and Crime Pattern Analysismentioning

confidence: 99%

Dynalink: A Framework for Dynamic Criminal Network Visualization

Park

Tsang

Brantingham

2012

2012 European Intelligence and Security Informatics Conference

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Abstract-Understanding the temporal development and patterns of criminal networks is important for law enforcement and intelligence agencies to investigate and prevent crimes. Extracting and visualizing criminal networks from a large amount of crime data has been a challenge over the past years. In particular, the visualization of the dynamic development of such networks over time has been difficult in many ways. Recent advancement of visual analytics provides new analytical reasoning tools to explore and analyze a large amount of data with interactive visual interfaces. By employing the ideas of visual analytics, we propose here a framework to visualize dynamic criminal networks, which is called Dynalink. The interactive and visual features of Dynalink can be useful in discovering and analyzing both relational and temporal patterns of criminal networks.

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“…We will use 2 km as the radius of the search area, meaning only crimes closer than 2 km from a route will be included in the algorithm. Previous studies [8] has suggested that most crimes can be found in less than 1 km from commonly used roads. However, that study was concerning with city areas.…”

Section: Analyze Routementioning

confidence: 99%

“…Iwanski et al [8] looked at the relationship of offender's location of crime and the travel routes an offender takes in their average day. The author had access to the offender's home, work location and location of the crimes they committed.…”

Section: B and Fosdickmentioning

confidence: 99%

Detecting Crime Series Based on Route Estimation and Behavioral Similarity

Borg

Boldt

Eliasson

2017

2017 European Intelligence and Security Informatics Conference (EISIC)

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Context. A majority of crimes are committed by a minority of offenders. Previous research has provided some support for the theory that serial offenders leave behavioral traces on the crime scene which could be used to link crimes to serial offenders. Objectives. Our objective was to investigate to what extent we could use route estimations and behavioral data to detect serial offenders. Method. To investigate if we could find crime routes with high similarity we ran experiments using behavioral data from authentic burglary reports. We also used used burglary reports from serial offenders to investigate to what extent we could detect serial offender crime routes. Results. The result show that crime series with the same offender on average had a higher behavioral similarity than random crime series. We also found crime series with high similarity without a known offender which could be interesting for law enforcement to investigate further. Conclusion. Our results suggest that it is possible to detect crime series committed by the same offender using behavioral data from the burglary. There is also potential for the law enforcement to detect interesting crime series with high similarity using behavioral similarity.

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Analyzing an Offender's Journey to Crime: A Criminal Movement Model (CriMM)

Cited by 19 publications

References 18 publications

Evaluating Temporal Analysis Methods Using Residential Burglary Data

Evaluating Temporal Analysis Methods Using Residential Burglary Data

Dynalink: A Framework for Dynamic Criminal Network Visualization

Detecting Crime Series Based on Route Estimation and Behavioral Similarity

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