Suggesting a Hybrid Approach: Mobile Apps with Big Data Analysis to Report and Prevent Crimes

  • Abdi FidowEmail author
  • Ahmed Hassan
  • Mahamed Iman
  • X. Cheng
  • M. Petridis
  • Clifford Sule
Part of the Security Informatics and Law Enforcement book series (SILE)


Conventional crime prediction techniques rely on location-specific historical crime data. Yet relying on historical crime data alone has deficiencies, as such data is limited in scope and often fails to capture the full complexity of crimes. This chapter proposes a novel approach to employ mobile applications with big data analysis for crime reporting and prevention using aggregate data from multiple sources, the Hybrid Smart Crime Reporting App (HIVICRA). It is an infographic intelligent crime-reporting analysis application that incorporates crime data sourced from local police, social media and crowdsourcing, including sentiment analysis of Twitter streams in conjunction with historical police crime datasets. An evaluation of the approach suggests that by combining sentiment analysis with smart crime reporting applications, it is possible to improve the forecasting of crime.


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Abdi Fidow
    • 1
    Email author
  • Ahmed Hassan
    • 1
  • Mahamed Iman
    • 1
  • X. Cheng
    • 1
  • M. Petridis
    • 1
  • Clifford Sule
    • 1
  1. 1.Middlesex UniversityLondonUK

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