Spatiotemporal Analysis of Web News Archives for Crime Prediction

In today’s world, security is the most prominent aspect which has been given higher priority. Despite the rapid growth and usage of digital devices, lucrative measurement of crimes in under-developing countries is still challenging. In this work, unstructural crime data (900 records) from the news a...

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Veröffentlicht in:Applied sciences Jg. 10; H. 22; S. 8220
Hauptverfasser: Umair, Areeba, Sarfraz, Muhammad Shahzad, Ahmad, Muhammad, Habib, Usman, Ullah, Muhammad Habib, Mazzara, Manuel
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Basel MDPI AG 01.11.2020
Schlagworte:
Accuracy
Algorithms
Clustering
Computational linguistics
Crime forecasting
crime prediction
Crime prevention
Criminal statistics
Data mining
Datasets
Digital archives
Geographic information systems
Information management
Language processing
Law enforcement
Machine learning
Methods
Natural language interfaces
Researchers
Spatial analysis
Spatial data
sustainable e-governance
sustainable information management
Technology application
Trends
Visualization
Web archiving
Pakistan
ISSN:2076-3417, 2076-3417
Online-Zugang:Volltext
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Zusammenfassung:In today’s world, security is the most prominent aspect which has been given higher priority. Despite the rapid growth and usage of digital devices, lucrative measurement of crimes in under-developing countries is still challenging. In this work, unstructural crime data (900 records) from the news archives of the previous eight years were extracted to predict the behavior of criminals’ networks and transform it into useful information using natural language processing (NLP). To estimate the next move of criminals in Pakistan, we performed hotspot-based spatial analysis. Later, this information is fed to two different classifiers for possible identification and prediction. We achieved the maximum accuracy of 92% using K-Nearest Neighbor (KNN) and 62% using the Random Forest algorithm. In terms of crimes, the results showed that the most prevalent crime events are robberies. Thus, the usage of digital information archives, spatial analysis, and machine learning techniques can open new ways of handling a peaceful and sustainable society in eradicating crimes for countries having paucity of financial resources.
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ISSN:2076-3417
2076-3417
DOI:10.3390/app10228220