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Analyzing Spatio-Temporal Effects of Social-Economic Factors on Crime

Authors:
Sebastian Baumbach
Nikita Sharma
Sheraz Ahmed
Andreas Dengel

Keywords: Staptio-temporal Data Mining; Crime Analysis; Prediction Models; Location Factors

Abstract:
Rampant increase in crime incidents has led to the need of crime analysis in greater detail. Existing crime analysis approaches focused on higher spatial granularity (i.e., country or state levels) and consider each data observation independent of each other. However, data can exhibit spatial and temporal relationships among them. Such interrelationships must be taken into consideration if precise crime analysis is intended. Therefore, a two-stage approach is proposed for predicting crime by analyzing its relationship with socio-economic factors: the first stage applies a spatio-temporal analysis on the data and these results are utilized for the spatio-temporal prediction, which forms the second stage. For evaluation, more than 450 different socio-economic factors and crime data for county level in Germany were analyzed. The evaluation results exhibit a mean absolute percentage error of 6.79% for spatio-temporal crime predictions, outperforming traditional regression techniques with an error rate of 37.1% - 37.8%.

Pages: 11 to 17

Copyright: Copyright (c) IARIA, 2018

Publication date: March 25, 2018

Published in: conference

ISSN: 2308-393X

ISBN: 978-1-61208-617-0

Location: Rome, Italy

Dates: from March 25, 2018 to March 29, 2018