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dc.rights.licenseAtribución-NoComercial-CompartirIgual 4.0 Internacional
dc.contributor.advisorGómez Jaramillo, Francisco Albeiro
dc.contributor.authorPulido Quintero, Cristian Alejandro
dc.date.accessioned2020-08-27T19:14:00Z
dc.date.available2020-08-27T19:14:00Z
dc.date.issued2020-05-26
dc.identifier.citationC. Pulido, "La importancia de la estructura de comunicación de una comunidad para la reducción del miedo al crimen" 2020
dc.identifier.urihttps://repositorio.unal.edu.co/handle/unal/78277
dc.description.abstractThe fear of crime is a determining factor in the security of a population, usually, through surveys, the relationships of this phenomenon with some social variables have been established and strategies to mitigate its consequences have been evaluated. Recently, a mathematical model was proposed for the propagation of fear of crime that allows the understanding of how this social construct arises from the characteristics of the population. In this document, the role of the communication structure in the fear of crime values was studied. Based on this model, modifications were made that take into account the type of connections between the members of the population and their exposure to multiple simultaneous communications. First, the effect of community-based communication networks frequently found in real societies was evaluated and then characterizing structures that allow the reduction of fear of crime, mainly for those with a higher victimization rate. The results suggest a determining role of the communication structure establishing different levels of fear of crime related to the type of connections that define people and particularly those structures that manage to establish a social cohesion are ideal for the task of reducing fear to crime values and its consequences.
dc.description.abstractEl miedo al crimen es un factor determinante en la seguridad de una población, usualmente, mediante encuestas se han establecido las relaciones de este fenómeno con algunas variables sociales y se han evaluado estrategias para mitigar sus consecuencias. Recientemente, se propuso un modelo matemático para la propagación del miedo al crimen, que permite entender como surge este constructo social a partir de características de la población. En este documento, se estudio el rol de la estructura de comunicación en los valores de miedo al crimen.Tomando como base dicho modelo, se realizaron modificaciones que tienen en cuenta el tipo de conexiones entre los miembros de la población y su exposición a multiples comunicaciones simultaneas. Primero se evaluó el efecto de las redes de comunicación basadas en comunidad, frecuentemente encontradas en las sociedades reales y luego caracterizando estructuras que permiten la reducción del miedo al crimen, principalmente, para aquellos con mayor tasa de victimización. Los resultados siguieren un rol determinante de la estructura de comunicación estableciendo distintos niveles de miedo al crimen relacionados con el tipo de conexiones, que de nen las personas y particularmente, aquellas estructuras que logran establecer una cohesión social, son ideales para la tarea de redución de los valores de miedo al crimen y sus consecuencias.
dc.format.extent113
dc.format.mimetypeapplication/pdf
dc.language.isospa
dc.rightsDerechos reservados - Universidad Nacional de Colombia
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/
dc.subject.ddc610 - Medicina y salud::613 - Salud y seguridad personal
dc.subject.ddc380 - Comercio , comunicaciones, transporte::384 - Comunicaciones
dc.titleLa importancia de la estructura de comunicación de una comunidad para la reducción del miedo al crimen
dc.typeOtro
dc.rights.spaAcceso abierto
dc.description.additionalLínea de Investigación: Seguridad Predictiva
dc.type.driverinfo:eu-repo/semantics/other
dc.type.versioninfo:eu-repo/semantics/acceptedVersion
dc.publisher.programBogotá - Ciencias - Maestría en Ciencias - Matemática Aplicada
dc.contributor.researchgroupCOMBIOS
dc.description.degreelevelMaestría
dc.publisher.departmentDepartamento de Matemáticas
dc.publisher.branchUniversidad Nacional de Colombia - Sede Bogotá
dc.relation.referencesW. G. Skogan and M. G. Max eld, Coping with crime : individual and neighborhood reactions / Wesley G. Skogan, Michael G. Max eld. Sage Publications Beverly Hills, 1981.
dc.relation.referencesJ. Garofalo, "The fear of crime: Causes and consequences," J. Crim. L. & Criminology, vol. 72, p. 839, 1981.
dc.relation.referencesD. A. Lewis, Fear of crime: Incivility and the production of a social problem. Routledge, 2017.
dc.relation.referencesV. Autores, "Encuesta de percepción ciudadana 2019." urlhttp://www.bogotacomovamos.org/documentos/encuesta-de-percepcion-ciudadana- 2019/, 2019.
dc.relation.referencesR. Hegselmann, U. Krause, et al., "Opinion dynamics and bounded con dence models, analysis, and simulation," Journal of arti cial societies and social simulation, vol. 5, no. 3, 2002.
dc.relation.referencesJ. A. Ho lyst, K. Kacperski, and F. Schweitzer, "Social impact models of opinion dynamics," in Annual Reviews Of Computational PhysicsIX, pp. 253{273, World Scienti c, 2001.
dc.relation.referencesR. B. Taylor and M. Hale, "Testing alternative models of fear of crime," J. Crim. L. & Criminology, vol. 77, p. 151, 1986.
dc.relation.referencesW. G. Skogan, "The impact of victimization on fear," Crime & Delinquency, vol. 33, no. 1, pp. 135-154, 1987.
dc.relation.referencesR. Prieto Curiel and S. Bishop, "Modelling the fear of crime," Proceedings of the Royal Society of London A: Mathematical, Physical and Engineering Sciences, vol. 473, no. 2203, 2017.
dc.relation.referencesC. Pulido and F. Gómez, "The role of communities in the fear of crime," in 2019 4th World Conference on Complex Systems (WCCS), pp. 1-6, IEEE, 2019.
dc.relation.referencesC. Pulido, J. Prieto, and F. Gómez, "How the social interactions in communities affect the fear of crime," Systems Research and Behavioral Science, vol. 36, no. 6, pp. 789-798, 2019.
dc.relation.referencesG. Cordner and B. K. Melekian, "Reducing fear of crime strategies for police," Office of Community Oriented Policing Services, 2010.
dc.relation.referencesJ. Henig and M. G. Max eld, "Reducing fear of crime: Strategies for intervention," Victimology, vol. 3, no. 3-4, pp. 297-313, 1978.
dc.relation.referencesG. L. Kelling, J. Q. Wilson, et al., "Broken windows," Atlantic monthly, vol. 249, no. 3, pp. 29-38, 1982.
dc.relation.referencesW. Skogan, The Various Meanings of Fear, pp. 131-140. Enke, 1993.
dc.relation.referencesC. Melde, M. T. Berg, and F.-A. Esbensen, "Fear, social interactions, and violence mitigation," Justice Quarterly, vol. 33, no. 3, pp. 481-509, 2016.
dc.relation.referencesR. P. Curiel and S. R. Bishop, "Fear of crime: the impact of different distributions of victimisation," Palgrave Communications, vol. 4, no. 1, p. 46, 2018.
dc.relation.referencesG. Canavos, P. Meyer, M. Spiegel, and S. Mendenhall, "Probabilidad y estadística," LICENCIATURA EN INGENIERÍA EN INFORMÁTICA, vol. 28, 1988
dc.relation.referencesM. McPherson, L. Smith-Lovin, and J. M. Cook, "Birds of a feather: Homophily in social networks," Annual review of sociology, vol. 27, no. 1, pp. 415-444, 2001.
dc.relation.referencesM. E. J. Newman, "Mixing patterns in networks," Phys. Rev. E, vol. 67, p. 026126, Feb 2003.
dc.relation.referencesF. Sabatini, "La segregación social del espacio en las ciudades de américa latina," tech. rep., Inter-American Development Bank, 2006.
dc.relation.referencesM. E. J. Newman, "Modularity and community structure in networks," Proceedings of the National Academy of Sciences, vol. 103, p. 8577^a\8582, May 2006.
dc.relation.referencesM. Girvan and M. E. Newman, "Community structure in social and biological networks," Proceedings of the national academy of sciences, vol. 99, no. 12, pp. 7821-7826, 2002.
dc.relation.referencesA. Sirbu, V. Loreto, V. D. Servedio, and F. Tria, "Opinion dynamics: models, extensions and external effects," in Participatory sensing, opinions and collective awareness, pp. 363-401, Springer, 2017.
dc.relation.referencesN. Gilbert, Agent-based models. Sage, 2008.
dc.relation.referencesG. Weisbuch, G. Deffuant, F. Amblard, and J.-P. Nadal, "Interacting agents and continuous opinions dynamics," in Heterogenous agents, interactions and economic performance, pp. 225-242, Springer, 2003.
dc.relation.referencesM. H. DeGroot, "Reaching a consensus," Journal of the American Statistical Association, vol. 69, no. 345, pp. 118-121, 1974.
dc.relation.referencesS. Boyd and L. Vandenberghe, Convex optimization. Cambridge university press, 2004.
dc.relation.referencesA. E. Eiben, J. E. Smith, et al., Introduction to evolutionary computing, vol. 53. Springer, 2003.
dc.relation.referencesD. Beasley, D. R. Bull, and R. R. Martin, "An overview of genetic algorithms: Part 1, fundamentals," University computing, vol. 15, no. 2, pp. 56-69, 1993.
dc.relation.referencesR. Muggah and K. A. Tobón, "Citizen security in latin america: Facts and fi gures," Strategic paper, vol. 33, 2018.
dc.relation.referencesP. González, Seguridad ciudadana. Colección Cuadernos de seguridad y defensa, FLACSO, Sede Académica Guatemala, 2003.
dc.relation.referencesE. C. NDUKWE, "Citizen security," Tell Magazine. September, vol. 28, pp. 60-61, 2009
dc.relation.referencesJ. M. McGloin, C. J. Sullivan, and L. W. Kennedy, When crime appears: The role of emergence. Routledge, 2011.
dc.relation.referencesD. Weatherburn et al., "What causes crime?," BOCSAR NSW Crime and Justice Bulletins, p. 11, 2001.
dc.relation.referencesG. S. Becker, "Crime and punishment: An economic approach," in The economic dimensions of crime, pp. 13-68, Springer, 1968.
dc.relation.referencesL. Goodstein and R. L. Shotland, "The crime causes crime model: A critical review of the relationships between fear of crime, bystander surveillance, and changes in the crime rate," Victimology, vol. 5, no. 2-4, pp. 133-151, 1980.
dc.relation.referencesD. F. Perilla Mesa et al., "El bronx: Una república independiente del crimen organizado (2002-2016)," Universidad Militar Nueva Granada, 2017.
dc.relation.referencesD. Watson, L. M. Johnson, N. Pino, and P. Morgan, "Police perceptions of residents in a high-crime area in trinidad and tobago: Community framing and crime wars," Criminology & Criminal Justice, p. 1748895819858372, 2019.
dc.relation.referencesR. B. Taylor and J. Covington, \"Community structural change and fear of crime," Social problems, vol. 40, no. 3, pp. 374-397, 1993.
dc.relation.referencesR. Bianchi, "Tourism and the globalisation of fear: Analysing the politics of risk and (in) security in global travel," Tourism and Hospitality Research, vol. 7, no. 1, pp. 64-74, 2006.
dc.relation.referencesB. Abizanda, J. Serra Hoffman, L. Marmolejo, and S. Duryea, "Citizen security: Conceptual framework and empirical evidence," tech. rep., Inter-American Development Bank, 2012.
dc.relation.referencesT. P. Caldeira, "Forti ed enclaves: The new urban segregation," in The urban sociology reader, pp. 419-427, Routledge, 2012.
dc.relation.referencesT. Chiricos, M. Hogan, and M. Gertz, "Racial composition of neighborhood and fear of crime," Criminology, vol. 35, no. 1, pp. 107-132, 1997.
dc.relation.referencesG. Cordner, "Reducing fear of crime: strategies for police. washington, dc: Us department of justice," 2010.
dc.relation.referencesC. d. C. de Bogotá, "Encuesta de percepción y victimización 2018-ii," 2019.
dc.relation.referencesD. Archer, R. Gartner, R. Akert, and T. Lockwood, "Cities and homicide: A new look at an old paradox," comparative Studies in Sociology, no. 1, 1978.
dc.relation.referencesV. Spicer, The Geometry of Fear; An Environmental perspective on Fear and the Perception of Crime. PhD thesis, Arts & Social Sciences: School of Criminology, 2012.
dc.relation.referencesK. F. Ferraro and R. L. Grange, "The measurement of fear of crime," Sociological inquiry, vol. 57, no. 1, pp. 70-97, 1987.
dc.relation.referencesJ. S. Zhao, B. Lawton, and D. Longmire, "An examination of the micro-level crime-fear of crime link," Crime & Delinquency, vol. 61, no. 1, pp. 19-44, 2015.
dc.relation.referencesJ. R. Porter, N. E. Rader, and J. S. Cossman, "Social disorganization and neighborhood fear: Examining the intersection of individual, community, and county characteristics," American Journal of Criminal Justice, vol. 37, no. 2, pp. 229-245, 2012.
dc.relation.referencesA. Boholm, "Comparative studies of risk perception: a review of twenty years of research," Journal of risk research, vol. 1, no. 2, pp. 135-163, 1998.
dc.relation.referencesR. B. Taylor, \Fear of crime, social ties, and collective efficacy: Maybe masquerading measurement, maybe deja vu all over again," Justice Quarterly, vol. 19, no. 4, pp. 773-792, 2002.
dc.relation.referencesJ. Jackson and E. Gray, "Functional fear and public insecurities about crime," The British Journal of Criminology, vol. 50, no. 1, pp. 1-22, 2009.
dc.relation.referencesL. Saad, "Worry about crime remains at last year s elevated levels," Gallup News Service, 2006.
dc.relation.referencesI. Cano and E. Rojido, "Mapeo de programas de prevención de homicidios en américa latina y el caribe," Laboratório de Análise da Violencia Universidade do Estado do Rio de Janeiro, 2016.
dc.relation.referencesV. Ordonez and T. L. Berg, "Learning high-level judgments of urban perception," in European Conference on Computer Vision, pp. 494-510, Springer, 2014.
dc.relation.referencesS. F. Acosta and J. E. Camargo, "City safety perception model based on visual content of street images," in 2018 IEEE International Smart Cities Conference (ISC2), pp. 1{8, IEEE, 2018.
dc.relation.referencesA. J. Park, Modeling the role of fear of crime in pedestrian navigation. PhD thesis, School of Interactive Arts & Technology-Simon Fraser University, 2008.
dc.relation.referencesL. Huddy, S. Feldman, T. Capelos, and C. Provost, "The consequences of terrorism: Disentangling the effects of personal and national threat," Political Psychology, vol. 23, no. 3, pp. 485-509, 2002.
dc.relation.referencesM. Warr, "Fear of crime in the united states: Avenues for research and policy," Criminal justice, vol. 4, no. 4, pp. 451-489, 2000.
dc.relation.referencesM. H. Moore and A. Braga, "The "bottom line" of policing: What citizens should value (and measure!) in police performance," in Washington, DC: Police Executive Research Forum http://www. policeforum. org/library/policeevaluation/BottomLineofPolicing. pdf, 2003.
dc.relation.referencesG. L. Kelling, T. Pate, D. Dieckman, and C. Brown, The Kansas City Preventive Patrol Experiment: A Tecnical Report. Police Foundation Washington, DC, 1974.
dc.relation.referencesW. Spelman and D. K. Brown, "Calling the police," in Washington, DC: Police Executive Research Forum, 1982.
dc.relation.referencesP. W. Greenwood, J. Chaiken, J. R. Petersilia, L. Prusoff, et al., "The criminal investigation process: Observations and analysis," The Rand Corporation, 1975.
dc.relation.referencesD. Dalgleish and A. Myhill, Reassuring the Public: A Review of the International Policing Interventions. Home Office Research, Development and Statistics Directorate, 2004.
dc.relation.referencesB. C. Welsh and D. P. Farrington, "Surveillance for crime prevention in public space: Results and policy choices in britain and america," Criminology & Public Policy, vol. 3, no. 3, pp. 497-526, 2004.
dc.relation.referencesM. C. Scheider, T. Rowell, and V. Bezdikian, "The impact of citizen perceptions of community policing on fear of crime: Findings from twelve cities," Police Quarterly, vol. 6, no. 4, pp. 363-386, 2003.
dc.relation.referencesD. D. Perkins and R. B. Taylor, "Ecological assessments of community disorder: Their relationship to fear of crime and theoretical implications," in Ecological research to promote social change, pp. 127-170, Springer, 2002.
dc.relation.referencesY. Xu, M. L. Fiedler, and K. H. Flaming, "Discovering the impact of community policing: The broken windows thesis, collective efficacy, and citizen s judgment," Journal of Research in crime and Delinquency, vol. 42, no. 2, pp. 147-186, 2005.
dc.relation.referencesA. Pate, M. A. Wycoff, W. G. Skogan, and L. W. Sherman, "Reducing fear of crime in houston and newark," Washington, DC: Police Foundation, 1986.
dc.relation.referencesM. Z. Ndii, E. Carnia, and A. K. Supriatna, "Mathematical models for the spread of rumors: a review," in Issues and Trends in Interdisciplinary Behavior and Social Science, pp. 65-73, CRC Press, 2018.
dc.relation.referencesC. E. Walters, M. M. Meslé, and I. M. Hall, "Modelling the global spread of diseases: A review of current practice and capability," Epidemics, vol. 25, pp. 1-8, 2018.
dc.relation.referencesM. Janssen and E. Ostrom, "Empirically based, agent-based models," Ecology and society, vol. 11, no. 2, 2006.
dc.relation.referencesP. Cane and H. Kritzer, The Oxford handbook of empirical legal research. OUP Oxford, 2010.
dc.relation.referencesD. McMillon, C. P. Simon, and J. Morenoff, "Modeling the underlying dynamics of the spread of crime," PloS one, vol. 9, no. 4, p. e88923, 2014.
dc.relation.referencesC. Zhang, M. Jain, R. Goyal, A. Sinha, and M. Tambe, "Learning, predicting and planning against crime: Demonstration based on real urban crime data," in Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems, pp. 1911-1912, International Foundation for Autonomous Agents and Multiagent Systems, 2015.
dc.relation.referencesZ. Liu and B. Hu, "Epidemic spreading in community networks," EPL (Europhysics Letters), vol. 72, no. 2, p. 315, 2005.
dc.relation.referencesX. Wu and Z. Liu, "How community structure in uences epidemic spread in social networks," Physica A: Statistical Mechanics and its Applications, vol. 387, no. 2-3, pp. 623-630, 2008.
dc.relation.referencesT. Newburn, "Social disadvantage: Crime and punishment," Social advantage and disadvantage, pp. 322-40, 2016.
dc.relation.referencesC. Palmer, A. Ziersch, K. Arthurson, and F. Baum, "Danger lurks around every corner: fear of crime and its impact on opportunities for social interaction in stigmatised australian suburbs," Urban Policy and Research, vol. 23, no. 4, pp. 393-411, 2005.
dc.relation.referencesX. Si, Y. Liu, and Z. Zhang, "Opinion dynamics in populations with implicit community structure," International Journal of modern physics C, vol. 20, no. 12, pp. 2013-2026, 2009.
dc.relation.referencesW. Ru and C. Li-Ping, "Opinion dynamics on complex networks with communities," Chinese Physics Letters, vol. 25, no. 4, p. 1502, 2008.
dc.relation.referencesF. D. Malliaros and M. Vazirgiannis, "Clustering and community detection in directed networks: A survey," Physics Reports, vol. 533, no. 4, pp. 95-142, 2013.
dc.relation.referencesC. Largeron, P.-N. Mougel, R. Rabbany, and O. R. Zaiane, "Generating attributed networks with communities," PLOS ONE, vol. 10, pp. 1-21, 04 2015.
dc.relation.referencesB. Kozma and A. Barrat, "Consensus formation on adaptive networks," Physical Review E, vol. 77, no. 1, p. 016102, 2008.
dc.relation.referencesC. Qian, J. Cao, J. Lu, and J. Kurths, "Adaptive bridge control strategy for opinion evolution on social networks," Chaos: An Interdisciplinary Journal of Nonlinear Science, vol. 21, no. 2, p. 025116, 2011.
dc.relation.referencesD. Stauffer and M. Sahimi, "Can a few fanatics infuence the opinion of a large segment of a society?," The European Physical Journal B, vol. 57, no. 2, pp. 147-152, 2007.
dc.relation.referencesP. Jia, A. MirTabatabaei, N. E. Friedkin, and F. Bullo, "Opinion dynamics and the evolution of social power in infuence networks," SIAM review, vol. 57, no. 3, pp. 367-397, 2015.
dc.relation.referencesR. T. Rockafellar and R. J.-B. Wets, Variational analysis, vol. 317. Springer Science & Business Media, 2009.
dc.relation.referencesJ. Saram aki, M. Kivel a, J.-P. Onnela, K. Kaski, and J. Kertész, "Generalizations of the clustering coefficient to weighted complex networks," Physical Review E, vol. 75, Feb 2007.
dc.relation.referencesW. J. C. W. H. Cunningham and W. R. P. A. Schrijver, "Combinatorial optimization," 1997.
dc.relation.referencesB. P. Veldkamp, "Computerized test construction," in International Encyclopedia of the Social Behavioral Sciences (Second Edition) (J. D. Wright, ed.), pp. 510 -514, Oxford: Elsevier, second edition ed., 2015.
dc.relation.referencesJ. Gomez, "Self adaptation of operator rates in evolutionary algorithms," in Genetic and Evolutionary Computation Conference, pp. 1162-1173, Springer, 2004.
dc.rights.accessrightsinfo:eu-repo/semantics/openAccess
dc.subject.proposalCommunication structure
dc.subject.proposalAlgoritmos evolutivos
dc.subject.proposalCohesión social
dc.subject.proposalEvolutionary algorithm
dc.subject.proposalFear of crime
dc.subject.proposalEstructura de comunicación
dc.subject.proposalMiedo al crimen
dc.subject.proposalReducing fear of crime
dc.subject.proposalReducción miedo al crimen.
dc.subject.proposalSocial cohesion
dc.type.coarhttp://purl.org/coar/resource_type/c_1843
dc.type.coarversionhttp://purl.org/coar/version/c_ab4af688f83e57aa
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