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Mining the Relationship BetweenCar Theft and Places of Social Interest in Santiago Chile

Published: 13 May 2019 Publication History

Abstract

Recent work suggests that certain places can be more attractive for car theft based how many people regularly visit them, as well as other factors. In this sense, we must also consider the city or district itself where vehicles are stolen. All cities have different cultural and socioeconomic characteristics that influence car theft patterns. In particular, the distribution of public services and places attract a large crowd could play a key role in the occurrence of car theft. Santiago, a city that displays drastic socioeconomic differences among its districts, presents increasingly-high car theft rates. This represents a serious issue for the city, as for any other major city, which –at least for Santiago– has not been analyzed in depth using quantitative approaches. In this work, we present a preliminary study of how places that create social interest, such as restaurants, bars, schools, and shopping malls, increase car theft frequency in Santiago. We also study if some types of places are more attractive than others for this type of crime. To evaluate this, we propose to analyze car theft points (CTP) from insurance companies and their relationship with places of social interest (PSI) extracted from Google Maps, using a proximity based approach. Our findings show a high correlation between CTP and PSI for all of the social interest categories that we studied in the different districts of the Santiago. In particular our work contributes to the understanding of the social factors that are associated to car thefts.

References

[1]
Carabineros de Chile. 2018. Statistical Report. http://dac.carabineros.cl/Reportes/reporte_noviembre_2018.html. {Online; accessed 22-January-2018}.
[2]
Instituto Nacional de Estadística de Chile. 2018. Parque de Vehículos. https://www.ine.cl/estadisticas/economicas/transporte-y-comunicaciones?categoria=Anuarios. {Online; accessed 22-January-2018}.
[3]
Biblioteca del Congreso Nacional. 2018. Región Metropolitana de Santiago. https://www.bcn.cl/siit/nuestropais/region13/index.htm. {Online; accessed 22-January-2018}.
[4]
Jerome H. Friedman, Jon Louis Bentley, and Raphael Ari Finkel. 1977. An Algorithm for Finding Best Matches in Logarithmic Expected Time. ACM Trans. Math. Softw. 3, 3 (Sept. 1977), 209–226.
[5]
Jerry Ratcliffe. 2010. Crime Mapping: Spatial and Temporal Challenges. In Handbook of Quantitative Criminology, Alex R. Piquero and David Weisburd (Eds.). Springer New York, New York, NY, 5–24.
[6]
Joel Stillerman and Rodrigo Salcedo. 2012. Transposing the Urban to the Mall: Routes, Relationships, and Resistance in Two Santiago, Chile, Shopping Centers. Journal of Contemporary Ethnography 41, 3 (June 2012), 309–336.
[7]
Isaac T. Van Patten, Jennifer McKeldin-Coner, and Deana Cox. 2009. A Microspatial Analysis of Robbery: Prospective Hot Spotting in a Small City. Crime Mapping: A Journal of Research and Practice 1, 1 (2009), 7–32. http://ivanpatt.asp.radford.edu/Research/Microspatial%2520Analysis%2520of%2520Robbery.pdf
[8]
Yuanyuan Mao, Shenzhi Dai, Jiajun Ding, Wei Zhu, Can Wang, and Xinyue Ye. 2018. Space Time Analysis of Vehicle Theft Patterns in Shanghai, China. https://www.mdpi.com/2220-9964/7/9/357/htm

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  • (2023)El robo de autos en Reynosa: análisis espacial desde la teoría de las actividades rutinarias y del patrón del crimenFrontera norte10.33679/rfn.v1i1.232435(1-25)Online publication date: 1-Jan-2023

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        cover image ACM Other conferences
        WWW '19: Companion Proceedings of The 2019 World Wide Web Conference
        May 2019
        1331 pages
        ISBN:9781450366755
        DOI:10.1145/3308560
        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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        • IW3C2: International World Wide Web Conference Committee

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        Association for Computing Machinery

        New York, NY, United States

        Publication History

        Published: 13 May 2019

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        Author Tags

        1. Google Maps
        2. car theft
        3. pattern extraction

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        WWW '19
        WWW '19: The Web Conference
        May 13 - 17, 2019
        San Francisco, USA

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        • (2023)El robo de autos en Reynosa: análisis espacial desde la teoría de las actividades rutinarias y del patrón del crimenFrontera norte10.33679/rfn.v1i1.232435(1-25)Online publication date: 1-Jan-2023

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