In July, we had a paper accepted for publication in Springer’s Social Network Analysis and Mining, entitled: Measuring UK crime gangs: a social network problem. This paper builds upon our previous work on social networks and crime analytics, using an interesting gun and gang crime dataset from Greater Manchester Police over a seven-year period.
The abstract of the paper is below; you can access it via Springer’s SharedIt service or our final pre-print on GitHub:
Measuring UK crime gangs: a social network problem
Giles Oatley and Tom Crick
This paper describes the output of a study to tackle the problem of gang-related crime in the UK; we present the intelligence and routinely-gathered data available to a UK regional police force, and describe an initial social network analysis of gangs in the Greater Manchester area of the UK between 2000 and 2006. By applying social network analysis techniques, we attempt to detect the birth of two new gangs based on local features (modularity, cliques) and global features (clustering coefficients). Thus for the future, identifying the changes in these can help us identify the possible birth of new gangs (sub-networks) in the social system. Furthermore, we study the dynamics of these networks globally and locally, and have identified the global characteristics that tell us that they are not random graphs—they are small world graphs—implying that the formation of gangs is not a random event. However, we are not yet able to conclude anything significant about scale-free characteristics due to insufficient sample size. A final analysis looks at gang roles and develops further insight into the nature of the different link types, referring to Klerks’ ‘third generation’ analysis, as well as a brief discussion of the potential UK policy applications of this work.
Keywords: Gangs; Gun crime; Scale-free networks; Small-world networks; Social distance; Communities; Crime policy
(also see: Publications)