Journal article
COMMUNITY DETECTION USING SPECTRAL CLUSTERING ON SPARSE GEOSOCIAL DATA
SIAM journal on applied mathematics, Vol.73(1), pp.67-83
01/01/2013
DOI: 10.1137/120882093
Abstract
In this article we identify social communities among gang members in the Hollenbeck policing district in Los Angeles, based on sparse observations of a combination of social interactions and geographic locations of the individuals. This information, coming from Los Angeles Police Department (LAPD) Field Interview cards, is used to construct a similarity graph for the individuals. We use spectral clustering to identify clusters in the graph, corresponding to communities in Hollenbeck, and compare these with the LAPD's knowledge of the individuals' gang membership. We discuss different ways of encoding the geosocial information using a graph structure and the influence on the resulting clusterings. Finally we analyze the robustness of this technique with respect to noisy and incomplete data, thereby providing suggestions about the relative importance of quantity versus quality of collected data.
Details
- Title: Subtitle
- COMMUNITY DETECTION USING SPECTRAL CLUSTERING ON SPARSE GEOSOCIAL DATA
- Creators
- Yves van Gennip - Univ Calif Los Angeles, Dept Math, Los Angeles, CA 90095 USABlake Hunter - Univ Calif Los Angeles, Dept Math, Los Angeles, CA 90095 USARaymond Ahn - Calif State Univ Long Beach, Dept Math, Long Beach, CA 90840 USAPeter Elliott - Univ Calif Los Angeles, Dept Math, Los Angeles, CA 90095 USAKyle Luh - Yale UniversityMegan Halvorson - University of California, IrvineShannon Reid - University of California, IrvineMatthew Valasik - University of California, IrvineJames Wo - University of California, IrvineGeorge E. Tita - University of California, IrvineAndrea L. Bertozzi - Univ Calif Los Angeles, Dept Math, Los Angeles, CA 90095 USAP. Jeffrey Brantingham - Univ Calif Los Angeles, Dept Anthropol, Los Angeles, CA 90095 USA
- Resource Type
- Journal article
- Publication Details
- SIAM journal on applied mathematics, Vol.73(1), pp.67-83
- Publisher
- Siam Publications
- DOI
- 10.1137/120882093
- ISSN
- 0036-1399
- eISSN
- 1095-712X
- Number of pages
- 17
- Grant note
- N000141010221; N000141210040 / ONR; Office of Naval Research FA9550-10-1-0569 / AFOSR MURI; United States Department of Defense; Air Force Office of Scientific Research (AFOSR); MURI DMS-1045536; DMS-0968309 / NSF; National Science Foundation (NSF)
- Language
- English
- Date published
- 01/01/2013
- Academic Unit
- Sociology and Criminology; Public Policy Center (Archive); Center for Social Science Innovation
- Record Identifier
- 9984282618502771
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