A systematic review of mobile phone data in crime applications: a coherent taxonomy based on data types and analysis perspectives, challenges, and future research …
Digital technologies have recently become more advanced, allowing for the development of
social networking sites and applications. Despite these advancements, phone calls and text …
social networking sites and applications. Despite these advancements, phone calls and text …
Information fusion in crime event analysis: A decade survey on data, features and models
Crime event analysis (CEA) has become increasingly important in assisting humans in
preventing future crimes. A fundamental challenge in the research community lies in the …
preventing future crimes. A fundamental challenge in the research community lies in the …
Auditing the fairness of place-based crime prediction models implemented with deep learning approaches
Place-based crime prediction models implemented with deep learning leverage the spatio-
temporal patterns of historical crimes, together with built-environment factors, to predict …
temporal patterns of historical crimes, together with built-environment factors, to predict …
Analysis of performance improvements and bias associated with the use of human mobility data in covid-19 case prediction models
The COVID-19 pandemic has mainstreamed human mobility data into the public domain,
with research focused on understanding the impact of mobility reduction policies as well as …
with research focused on understanding the impact of mobility reduction policies as well as …
Understanding the role of mobility in the recorded levels of violent crimes during COVID-19 pandemic: a case study of Tamil Nadu, India
K Paramasivan, S Jaiswal, R Subburaj, N Sudarsanam - Crime Science, 2024 - Springer
Abstract Purpose/Goal This research investigates the potential link between mobility and
violent crimes in Tamil Nadu, India, using an empirical study centred on the COVID-19 …
violent crimes in Tamil Nadu, India, using an empirical study centred on the COVID-19 …
A deep multi-scale neural networks for crime hotspot mapping prediction
Prediction of high-risk areas for urban crime is of great significance for maintaining public
safety and sustainable development. However, existing approaches are deficient in …
safety and sustainable development. However, existing approaches are deficient in …
From mobility to crime: Collective patterns of human mobility and gun violence in Baltimore City
X Situ - Journal of Criminal Justice, 2024 - Elsevier
Purpose: In this research, I investigated the link between collective mobility patterns—
specifically inward population flow and residential mobility—and changes in reported gun …
specifically inward population flow and residential mobility—and changes in reported gun …
Revisiting Synthetic Human Trajectories: Imitative Generation and Benchmarks Beyond Datasaurus
B Deng, X Jing, T Yang, B Qu… - arXiv preprint arXiv …, 2024 - arxiv.org
Human trajectory data, which plays a crucial role in various applications such as crowd
management and epidemic prevention, is challenging to obtain due to practical constraints …
management and epidemic prevention, is challenging to obtain due to practical constraints …
Improving the Fairness of Deep-Learning, Short-term Crime Prediction with Under-reporting-aware Models
J Wu, V Frias-Martinez - arXiv preprint arXiv:2406.04382, 2024 - arxiv.org
Deep learning crime predictive tools use past crime data and additional behavioral datasets
to forecast future crimes. Nevertheless, these tools have been shown to suffer from unfair …
to forecast future crimes. Nevertheless, these tools have been shown to suffer from unfair …
Network-Based Transfer Learning Helps Improve Short-Term Crime Prediction Accuracy
J Wu, V Frias-Martinez - arXiv preprint arXiv:2406.06645, 2024 - arxiv.org
Deep learning architectures enhanced with human mobility data have been shown to
improve the accuracy of short-term crime prediction models trained with historical crime …
improve the accuracy of short-term crime prediction models trained with historical crime …