Exploiting place features in link prediction on location-based social networks
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Human mobility, social ties, and link prediction
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
SPORS: A Suspect Recommendation System Based on Offenders' Reconstructed Spatial Profile
EISIC '12 Proceedings of the 2012 European Intelligence and Security Informatics Conference
Investigating Organized Crime Groups: A Social Network Analysis Perspective
ASONAM '12 Proceedings of the 2012 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2012)
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Individuals frequently have routine daily activities that require commuting between several places, such as their home, work, shopping centres and recreational facilities. According to Crime Pattern Theory, offenders most likely commit opportunistic crimes, including serial and violent crimes, within their Activity Space, that is the space that they visit most frequently during the course of their daily routine activities, since they are aware of the opportunities and risks within these spaces. However, others within the social network of an offender can introduce the offender to new opportunities outside of his Activity Space, a phenomenon that Crime Pattern Theory does not address. This paper explores an important and interesting question about social networks: What is the relation between social and spatial distance of actors? We study this question in the context of crime and co-offending networks to better understand the impact of an offender's social network on the Activity Space of the offender. Our experiments on real-life crime data show that there is a strong correlation between social and spatial distance of offenders: offenders who are socially close are also spatially close.