In recent years there has been a growing use of big data analytical approaches to map and understand crime patterns. Various approaches have been suggested from geospatial to temporal methods, as well as Social Network Analysis and crime linkage programs. Large databases have been sourced and programs tested on the predictive validity of several approaches, with varying degrees of success. A main focus of the Special Issue is not only to provide insight into novel approaches and advances in tackling crime; but to provide outputs that are clear for end-users (i.e., law enforcement organisations) to implement and put into practice. The integration of an expert’s knowledge alongside applied, integrated systems of understanding is a primary focus for bridging the gap between academic and practitioner approaches. Authors are therefore encouraged to provide an overview of their statistical or methodological approach that is ‘fit-for-purpose’ of allowing non-specialist audiences to understand and apply the methods.
Topics can take a variety of approaches to tackling crime; these are some of the proposed areas:
- Big data analytical approaches to crime prevention
- Artificial Intelligence / Machine learning
- Temporal / Sequence Analytical approaches
- Geospatial analyses
- (Social) Network Analysis
- Crime linkage / Visual Clustering Algorithms
- Text mining / Interrogation analytical approaches
- Bayesian analytical approaches
Please note: any area of crime or criminal investigation can be used, from detection of crime hotspots, through to interrogation and processing of evidence.
Submission deadline: 30 Sept 2019
More details: https://t.co/DZmXNj5qyT