Estudio de los robos en Pereira mediante la detección y dinámica de patrones en redes espacio temporales
ilustraciones, diagramas, planos
- Autores:
-
Quintero Martinez, Miguel Ángel
- Tipo de recurso:
- Fecha de publicación:
- 2023
- Institución:
- Universidad Nacional de Colombia
- Repositorio:
- Universidad Nacional de Colombia
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/84765
- Palabra clave:
- Robo
Delitos contra la propiedad
Vandalismo
Robbery
Offenses against property
Vandalism
Redes Complejas
Redes de Eventos
Motifs
Datos espacio-temporales
Clusterización
Centralidad
Complex Networks
Event Networks
Spatio-Temporal Data
Clustering
Centrality
- Rights
- openAccess
- License
- Atribución-NoComercial 4.0 Internacional
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Estudio de los robos en Pereira mediante la detección y dinámica de patrones en redes espacio temporales |
| dc.title.translated.eng.fl_str_mv |
Study of thefts in Pereira through the detection and dynamics of patterns in spatial-temporal networks |
| title |
Estudio de los robos en Pereira mediante la detección y dinámica de patrones en redes espacio temporales |
| spellingShingle |
Estudio de los robos en Pereira mediante la detección y dinámica de patrones en redes espacio temporales Robo Delitos contra la propiedad Vandalismo Robbery Offenses against property Vandalism Redes Complejas Redes de Eventos Motifs Datos espacio-temporales Clusterización Centralidad Complex Networks Event Networks Spatio-Temporal Data Clustering Centrality |
| title_short |
Estudio de los robos en Pereira mediante la detección y dinámica de patrones en redes espacio temporales |
| title_full |
Estudio de los robos en Pereira mediante la detección y dinámica de patrones en redes espacio temporales |
| title_fullStr |
Estudio de los robos en Pereira mediante la detección y dinámica de patrones en redes espacio temporales |
| title_full_unstemmed |
Estudio de los robos en Pereira mediante la detección y dinámica de patrones en redes espacio temporales |
| title_sort |
Estudio de los robos en Pereira mediante la detección y dinámica de patrones en redes espacio temporales |
| dc.creator.fl_str_mv |
Quintero Martinez, Miguel Ángel |
| dc.contributor.advisor.none.fl_str_mv |
Bohorquez Castañeda, Martha Patricia Renteria Ramos, Rafael Ricardo |
| dc.contributor.author.none.fl_str_mv |
Quintero Martinez, Miguel Ángel |
| dc.subject.lemb.spa.fl_str_mv |
Robo Delitos contra la propiedad Vandalismo |
| topic |
Robo Delitos contra la propiedad Vandalismo Robbery Offenses against property Vandalism Redes Complejas Redes de Eventos Motifs Datos espacio-temporales Clusterización Centralidad Complex Networks Event Networks Spatio-Temporal Data Clustering Centrality |
| dc.subject.lemb.eng.fl_str_mv |
Robbery Offenses against property Vandalism |
| dc.subject.proposal.spa.fl_str_mv |
Redes Complejas Redes de Eventos Motifs Datos espacio-temporales Clusterización Centralidad |
| dc.subject.proposal.eng.fl_str_mv |
Complex Networks Event Networks Spatio-Temporal Data Clustering Centrality |
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ilustraciones, diagramas, planos |
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2023 |
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2023-10-05T15:44:20Z |
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2023-10-05T15:44:20Z |
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2023 |
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Trabajo de grado - Maestría |
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info:eu-repo/semantics/masterThesis |
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Universidad Nacional de Colombia |
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Repositorio Institucional Universidad Nacional de Colombia |
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Wikimedia Commons. Modificado por corso de [2] (gnufdl), cc by-sa 4.0 lt;https://creativecommons.org/licenses/by-sa/4.0gt;, via wikimedia commons, 2023. lan Miguel Forero Sanabria, Martha Patricia Bohorquez Castañeda, Rafael Ricar do Rentería Ramos, and Jorge Mateu. Identification of patterns for space-time event networks. Applied Network Science, 7(1):1–24, 2022. Toby Davies and Elio Marchione. Event networks and the identification of crime pattern motifs. PloS one, 10(11):e0143638, 2015. tefano Boccaletti, Ginestra Bianconi, Regino Criado, Charo I Del Genio, Jesús Gómez Gardenes, Miguel Romance, Irene Sendina-Nadal, Zhen Wang, and Massimiliano Zanin. The structure and dynamics of multilayer networks. Physics reports, 544(1):1–122, 2014. Laura Lotero, Rafael G. Hurtado, Luis Mario Floría, and Jesús Gómez-Gardeñes. Rich do not rise early: spatio-temporal patterns in the mobility networks of different socio-economic classes. Royal Society open science, 3(10):150654, 2016. Ron Milo, Shai Shen-Orr, Shalev Itzkovitz, Nadav Kashtan, Dmitri Chklovskii, and Uri Alon. Network motifs: simple building blocks of complex networks. Science, 298(5594):824–827, 2002. Nadav Kashtan, Shalev Itzkovitz, Ron Milo, and Uri Alon. Efficient sampling algorithm for estimating subgraph concentrations and detecting network motifs. Bioinformatics, 20(11):1746–1758, 2004. Sebastian Wernicke. Efficient detection of network motifs. IEEE/ACM transactions on computational biology and bioinformatics, 3(4):347–359, 2006. Thaddeus Vincenty. Direct and inverse solutions of geodesics on the ellipsoid with application of nested equations. Survey review, 23(176):88–93, 1975. Rachel Boba. Crime analysis with crime mapping. Sage publications, 2016. Marcus Felson and Rachel Boba. Crime and everyday life. Sage, 2010. Paul Cozens, Terence Love, and Brent Davern. Geographical juxtaposition: A new direction in cpted. Social Sciences, 8(9):252, 2019. Sergey Dorogovtsev, Alexander Goltsev, and José Mendes. Critical phenomena in complex networks. Reviews of Modern Physics, 80(4):1275, 2008. Katarzyna Sznajd-Weron and Jozef Sznajd. Opinion evolution in closed community. International Journal of Modern Physics C, 11(06):1157–1165, 2000. Mark Newman. Networks. Oxford university press, Ann Arbor, 2018 Mark Newman, Albert-László Barabási, and Duncan J. Watts. The Structure and Dynamics of Networks. Princeton University Press, Princeton, 2006. Albert-László Barabási. Network science. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 371(1987), 2013. Ernesto Estrada. The Structure of Complex Networks: Theory and Applications. Oxford University Press, Inc., USA, 2011. Sergey Dorogovtsev and Jose Mendes. Evolution of networks. Advances in physics, 51(4):1079–1187, 2002 Vito Latora, Vincenzo Nicosia, and Giovanni Russo. Complex Networks: Principles, Methods and Applications. Cambridge University Press, USA, 1st edition, 2017. Linton Freeman. The development of social network analysis. A Study in the Sociology of Science, 1, 2004 Stanley Wasserman and Katherine Faust. Social Network Analysis: Methods and Applications. Structural Analysis in the Social Sciences. Cambridge University Press, 1994. Ernesto Estrada and Philip A Knight. A first course in network theory. Oxford University Press, USA, 2015. Miguel Ángel Quintero. Ising Model applied to Complex Networks: Opinion formation in dialectic processes. Tesis de pregrado inédita, Universidad Nacional de Colombia, 2019. Paul Erdos and Alfréd Rényi. On the evolution of random graphs. ˝ Publications of the Mathematical Institute of the Hungarian Academy of Sciences, 5(1):17–60, 1960. Duncan J Watts and Steven H Strogatz. Collective dynamics of ‘small-world’networks. nature, 393(6684):440, 1998. Albert-László Barabási and Réka Albert. Emergence of scaling in random networks. science, 286(5439):509–512, 1999. Lawrence Page, Sergey Brin, Rajeev Motwani, and Terry Winograd. The pagerank citation ranking: Bringing order to the web. Technical report, Stanford InfoLab, 1999. Anna Broido and Aaron Clauset. Scale-free networks are rare. Nature communications, 10(1):1017, 2019. Stuart Lloyd. Least squares quantization in pcm. IEEE Transactions on Information Theory, 28(2):129–137, 1982. Martin Ester, Hans-Peter Kriegel, Jörg Sander, Xiaowei Xu, et al. A density-based algorithm for discovering clusters in large spatial databases with noise. In kdd, volume 96, pages 226–231, 1996. Jacques Dutka. The early history of the factorial function. Archive for history of exact sciences, pages 225–249, 1991. Departamento Administrativo Nacional de Estadística (DANE). Censo nacional de población y vivienda 2018, 2018. Williams Gilberto Jiménez-García. Hacia una tipología de lugares peligrosos. caso de estudio de la comuna 11 de dosquebradas, colombia. Revista Criminalidad, 56(1):133– 156, 2014. Municipio de Pereira. Plan integral de seguridad y convivencia ciudadana, 2020. Aaron Clauset, Cosma Rohilla Shalizi, and M. E. J. Newman. Power-law distributions in empirical data. SIAM Review, 51(4):661–703, 2009. |
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Pereira |
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Colombia |
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Bogotá - Ciencias - Maestría en Ciencias - Estadística |
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Atribución-NoComercial 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Bohorquez Castañeda, Martha Patricia2e2e02de049d58b3081d25a3e7e00efdRenteria Ramos, Rafael Ricardod51216b694a399b26350e96b5a18a841Quintero Martinez, Miguel Ángelf8ec9c5110ce812eb0c4ddefa498dab02023-10-05T15:44:20Z2023-10-05T15:44:20Z2023https://repositorio.unal.edu.co/handle/unal/84765Universidad Nacional de ColombiaRepositorio Institucional Universidad Nacional de Colombiahttps://repositorio.unal.edu.co/ilustraciones, diagramas, planosEste trabajo presenta un análisis espacio-temporal del crimen en la ciudad de Pereira, Colombia, mediante un modelamiento por medio de redes complejas. Se construye una red de eventos criminales considerando cada crimen como un nodo y las relaciones espaciales y temporales entre ellos como aristas. Los datos utilizados para este estudio consisten en hurtos reportados al departamento de policía local entre 2018 y 2021. Se estudia la estructura de la red mediante la identificación de patrones recurrentes, conocidos como motifs, que describen comportamientos emergentes del crimen. Para mejorar la eficiencia computacional para la detección de motifs, se propone una metodología que utiliza la estructura de estos subgrafos que optimiza el conteo dentro del algoritmo. Se utilizan algoritmos de clusterización en los datos para identificar las áreas que tienen patrones espacio-temporales similares de delincuencia. Se observó que una distribución log-normal se ajustaba adecuadamente a la distribución del grado de la red de eventos, permitiendo definir la distancia en la que dos sucesos pueden estar relacionados en el espacio. Los resultados muestran que la metodología propuesta es eficaz en la identificación de motifs que capturan patrones espacio-temporales del hurto de personas. Este estudio demuestra la utilidad del análisis de redes en la modelización del crimen y aporta ideas que pueden servir de base a las estrategias de prevención de la delincuencia. (Texto tomado de la fuente)This work presents a spatio-temporal analysis of crime in the city of Pereira, Colombia, using a complex network modeling approach. A network of criminal events is constructed considering each crime as a node and the spatial and temporal relationships between them as edges. The data used for this study consists of thefts reported to the local police department between 2018 and 2021. The network structure is studied by identifying recurring patterns, known as motifs, which describe emergent crime behaviors. To improve computational efficiency for motif detection a methodology is proposed that uses the structure of these subgraphs to optimize the count within the algorithm. Clustering algorithms are used on the data to identify areas that have similar spatio-temporal patterns of crime. A log-normal distribution was found to adequately fit the event network degree distribution, allowing to define the appropriate distance in which two events can be related in space. The results show that the proposed methodology is effective in identifying motifs that capture spatio-temporal patterns of crime. This study demonstrates the usefulness of network analysis in crime modeling and provides insights that can inform crime prevention strategiesMaestríaxv, 85 páginasapplication/pdfspaUniversidad Nacional de ColombiaBogotá - Ciencias - Maestría en Ciencias - EstadísticaFacultad de CienciasBogotá, ColombiaUniversidad Nacional de Colombia - Sede BogotáEstudio de los robos en Pereira mediante la detección y dinámica de patrones en redes espacio temporalesStudy of thefts in Pereira through the detection and dynamics of patterns in spatial-temporal networksTrabajo de grado - Maestríainfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/acceptedVersionTexthttp://purl.org/redcol/resource_type/TMPereiraColombiaWikimedia Commons. Modificado por corso de [2] (gnufdl), cc by-sa 4.0 lt;https://creativecommons.org/licenses/by-sa/4.0gt;, via wikimedia commons, 2023.lan Miguel Forero Sanabria, Martha Patricia Bohorquez Castañeda, Rafael Ricar do Rentería Ramos, and Jorge Mateu. Identification of patterns for space-time event networks. Applied Network Science, 7(1):1–24, 2022.Toby Davies and Elio Marchione. Event networks and the identification of crime pattern motifs. PloS one, 10(11):e0143638, 2015.tefano Boccaletti, Ginestra Bianconi, Regino Criado, Charo I Del Genio, Jesús Gómez Gardenes, Miguel Romance, Irene Sendina-Nadal, Zhen Wang, and Massimiliano Zanin. The structure and dynamics of multilayer networks. Physics reports, 544(1):1–122, 2014.Laura Lotero, Rafael G. Hurtado, Luis Mario Floría, and Jesús Gómez-Gardeñes. Rich do not rise early: spatio-temporal patterns in the mobility networks of different socio-economic classes. Royal Society open science, 3(10):150654, 2016.Ron Milo, Shai Shen-Orr, Shalev Itzkovitz, Nadav Kashtan, Dmitri Chklovskii, and Uri Alon. Network motifs: simple building blocks of complex networks. Science, 298(5594):824–827, 2002.Nadav Kashtan, Shalev Itzkovitz, Ron Milo, and Uri Alon. Efficient sampling algorithm for estimating subgraph concentrations and detecting network motifs. Bioinformatics, 20(11):1746–1758, 2004.Sebastian Wernicke. Efficient detection of network motifs. IEEE/ACM transactions on computational biology and bioinformatics, 3(4):347–359, 2006.Thaddeus Vincenty. Direct and inverse solutions of geodesics on the ellipsoid with application of nested equations. Survey review, 23(176):88–93, 1975.Rachel Boba. Crime analysis with crime mapping. Sage publications, 2016.Marcus Felson and Rachel Boba. Crime and everyday life. Sage, 2010.Paul Cozens, Terence Love, and Brent Davern. Geographical juxtaposition: A new direction in cpted. Social Sciences, 8(9):252, 2019.Sergey Dorogovtsev, Alexander Goltsev, and José Mendes. Critical phenomena in complex networks. Reviews of Modern Physics, 80(4):1275, 2008.Katarzyna Sznajd-Weron and Jozef Sznajd. Opinion evolution in closed community. International Journal of Modern Physics C, 11(06):1157–1165, 2000.Mark Newman. Networks. Oxford university press, Ann Arbor, 2018Mark Newman, Albert-László Barabási, and Duncan J. Watts. The Structure and Dynamics of Networks. Princeton University Press, Princeton, 2006.Albert-László Barabási. Network science. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 371(1987), 2013.Ernesto Estrada. The Structure of Complex Networks: Theory and Applications. Oxford University Press, Inc., USA, 2011.Sergey Dorogovtsev and Jose Mendes. Evolution of networks. Advances in physics, 51(4):1079–1187, 2002Vito Latora, Vincenzo Nicosia, and Giovanni Russo. Complex Networks: Principles, Methods and Applications. Cambridge University Press, USA, 1st edition, 2017.Linton Freeman. The development of social network analysis. A Study in the Sociology of Science, 1, 2004Stanley Wasserman and Katherine Faust. Social Network Analysis: Methods and Applications. Structural Analysis in the Social Sciences. Cambridge University Press, 1994.Ernesto Estrada and Philip A Knight. A first course in network theory. Oxford University Press, USA, 2015.Miguel Ángel Quintero. Ising Model applied to Complex Networks: Opinion formation in dialectic processes. Tesis de pregrado inédita, Universidad Nacional de Colombia, 2019.Paul Erdos and Alfréd Rényi. On the evolution of random graphs. ˝ Publications of the Mathematical Institute of the Hungarian Academy of Sciences, 5(1):17–60, 1960.Duncan J Watts and Steven H Strogatz. Collective dynamics of ‘small-world’networks. nature, 393(6684):440, 1998.Albert-László Barabási and Réka Albert. Emergence of scaling in random networks. science, 286(5439):509–512, 1999.Lawrence Page, Sergey Brin, Rajeev Motwani, and Terry Winograd. The pagerank citation ranking: Bringing order to the web. Technical report, Stanford InfoLab, 1999.Anna Broido and Aaron Clauset. Scale-free networks are rare. Nature communications, 10(1):1017, 2019.Stuart Lloyd. Least squares quantization in pcm. IEEE Transactions on Information Theory, 28(2):129–137, 1982.Martin Ester, Hans-Peter Kriegel, Jörg Sander, Xiaowei Xu, et al. A density-based algorithm for discovering clusters in large spatial databases with noise. In kdd, volume 96, pages 226–231, 1996.Jacques Dutka. The early history of the factorial function. Archive for history of exact sciences, pages 225–249, 1991.Departamento Administrativo Nacional de Estadística (DANE). Censo nacional de población y vivienda 2018, 2018.Williams Gilberto Jiménez-García. Hacia una tipología de lugares peligrosos. caso de estudio de la comuna 11 de dosquebradas, colombia. Revista Criminalidad, 56(1):133– 156, 2014.Municipio de Pereira. Plan integral de seguridad y convivencia ciudadana, 2020.Aaron Clauset, Cosma Rohilla Shalizi, and M. E. J. Newman. Power-law distributions in empirical data. SIAM Review, 51(4):661–703, 2009.RoboDelitos contra la propiedadVandalismoRobberyOffenses against propertyVandalismRedes ComplejasRedes de EventosMotifsDatos espacio-temporalesClusterizaciónCentralidadComplex NetworksEvent NetworksSpatio-Temporal DataClusteringCentralityORIGINAL1016076555.2023.pdf1016076555.2023.pdfTesis de Maestría en Ciencias - Estadísticaapplication/pdf4926845https://repositorio.unal.edu.co/bitstream/unal/84765/2/1016076555.2023.pdfefc9c636fa0b561d56f3b42a06ab8fdfMD52THUMBNAIL1016076555.2023.pdf.jpg1016076555.2023.pdf.jpgGenerated Thumbnailimage/jpeg4814https://repositorio.unal.edu.co/bitstream/unal/84765/3/1016076555.2023.pdf.jpgd4bda4cbd097254a7a0151d1b857fd6aMD53LICENSElicense.txtlicense.txttext/plain; charset=utf-85879https://repositorio.unal.edu.co/bitstream/unal/84765/1/license.txteb34b1cf90b7e1103fc9dfd26be24b4aMD51unal/84765oai:repositorio.unal.edu.co:unal/847652023-10-05 23:03:47.017Repositorio Institucional Universidad Nacional de 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