Limit this search to....

Using Open Data to Detect Organized Crime Threats: Factors Driving Future Crime 2017 Edition
Contributor(s): Larsen, Henrik Legind (Editor), Blanco, José María (Editor), Pastor Pastor, Raquel (Editor)
ISBN: 3319527029     ISBN-13: 9783319527024
Publisher: Springer
OUR PRICE:   $132.99  
Product Type: Hardcover - Other Formats
Published: April 2017
Qty:
Additional Information
BISAC Categories:
- Social Science | Criminology
- Computers | Databases - Data Mining
- Mathematics | Probability & Statistics - General
Dewey: 006.312
Physical Information: 0.69" H x 6.14" W x 9.21" (1.31 lbs) 282 pages
 
Descriptions, Reviews, Etc.
Publisher Description:

This work provides an innovative look at the use of open data for extracting information to detect and prevent crime, and also explores the link between terrorism and organized crime. In counter-terrorism and other forms of crime prevention, foresight about potential threats is vitally important and this information is increasingly available via electronic data sources such as social media communications. However, the amount and quality of these sources is varied, and researchers and law enforcement need guidance about when and how to extract useful information from them.

The emergence of these crime threats, such as communication between organized crime networks and radicalization towards terrorism, is driven by a combination of political, economic, social, technological, legal and environmental factors. The contributions to this volume represent a major step by researchers to systematically collect, filter, interpret, and use the information available. For the purposes of this book, the only data sources used are publicly available sources which can be accessed legally and ethically.

This work will be of interest to researchers in criminology and criminal justice, particularly in police science, organized crime, counter-terrorism and crime science. It will also be of interest to those in related fields such as applications of computer science and data mining, public policy, and business intelligence.