The article uses a conceptual framework to review empirical evidence and some 180 articles
related to the opportunities and threats of Big Data Analytics for international development …

The primary objective of this study is to accumulate, summarize, and evaluate the state-of-
the-art for spatio-temporal crime hotspot detection and prediction techniques by conducting …

Spatiotemporal data mining (STDM) discovers useful patterns from the dynamic interplay
between space and time. Several available surveys capture STDM advances and report a …

In this paper, we present a novel approach to predict crime in a geographic space from
multiple data sources, in particular mobile phone and demographic data. The main …

Crime is one of the most important social problems in the country, affecting public safety,
children development, and adult socioeconomic status. Understanding what factors cause …

The unprecedented availability of large-scale human behavioral data is profoundly
changing the world we live in. Researchers, companies, governments, financial institutions …

Contagious diseases pose significant challenges to public healthcare systems all over the
world. The rise in emerging contagious and infectious diseases has led to calls for the use of …

In this paper, a detailed study on crime classification and prediction using deep learning
architectures is presented. We examine the effectiveness of deep learning algorithms in this …

Crime is a complex social issue impacting a considerable number of individuals within a
society. Preventing and reducing crime is a top priority in many countries. Given limited …

Research into recidivism risk prediction in the criminal justice system has garnered
significant attention from HCI, critical algorithm studies, and the emerging field of human-AI …