Mining location-based social networks for criminal activity prediction

Yu Yueh Huang, Cheng-Te Li, Shyh Kang Jeng

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

The problem of finding critical features for different crime types has been the focus in the field of environmental criminology because crime would lead to bad zoning in urban areas. However, conventional analysis ignores social dynamics of human beings. With the increasing growth of location-based social networks, the fine-grained data associated with social connections and the geographical information of users are available for representing the spatio-social dynamics of people. In this work, we devise a series of features to characterize an urban climate by data obtained from Foursquare and Gowalla in San Francisco. As for crime, we take use of crime data provided by the authorities. The features we mined are based on two general signals: geographical features that capture the distribution of various types of venues in urban areas, and social features that model the topological interactions between people in a region. We use these features to analyze and detect urban areas with high crime activities. The experimental results show the effectiveness of the proposed features on five different crime types and encourage future advanced criminal analysis using location-based social network data.

Original languageEnglish
Title of host publication2015 24th Wireless and Optical Communication Conference, WOCC 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages185-189
Number of pages5
ISBN (Electronic)9781479988549
DOIs
Publication statusPublished - 2015 Dec 2
Event24th Wireless and Optical Communication Conference, WOCC 2015 - Taipei, Taiwan
Duration: 2015 Oct 232015 Oct 24

Publication series

Name2015 24th Wireless and Optical Communication Conference, WOCC 2015

Other

Other24th Wireless and Optical Communication Conference, WOCC 2015
CountryTaiwan
CityTaipei
Period15-10-2315-10-24

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications

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  • Cite this

    Huang, Y. Y., Li, C-T., & Jeng, S. K. (2015). Mining location-based social networks for criminal activity prediction. In 2015 24th Wireless and Optical Communication Conference, WOCC 2015 (pp. 185-189). [7346202] (2015 24th Wireless and Optical Communication Conference, WOCC 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/WOCC.2015.7346202