Design agent based model to study the impact of social cohesion and victimization in the criminal behavior
Main Article Content
Keywords
Agent based Modelling, Social Cohesion, Social Networks, Cluster Coefficient, PECS
Abstract
In this research the construction of an agent-based model is proposed to study the impact of social cohesion and victimization in the process of decision making of a criminal. Modeling criminological aspects-established from theories of social disorder and routine activities in an architecture of artificial intelligence PECS (Physic, Emotion, Cognitive, Social), in order to articulate all dimensions involved in the construction of the decision. Social cohesion will be represented by social networks following the experiment done by Watts - Strogatz, and victimization as a cumulative result of previous victimizations. The results obtained in the simulation allowed to replicate social behavior main characteristics of a criminal Actor, because in them, the importance of the perception of social cohesion on the memory of victimization generated by past criminal events are highlighted. Elements that are consistent with the empirical evidence of the theoretical principles established in social disorder and routine actions.
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References
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[2] J. R. Hipp, “Micro-structure in micro-neighborhoods: a new social distance measure, and its effect on individual and aggregated perceptions of crime and disorder,” Social Networks, vol. 32, no. 2, pp. 148–159, 2010. 107, 118, 121, 123
[3] D. Black, The behavior of law. Emerald Group Publishing, 2010. 107
[4] A. E. Bottoms and P. Wiles, Environmental criminology, M. Mike, M. Rod, and R. Robert, Eds. Oxford University Press, 2002. 107, 108
[5] R. J. Sampson, S. W. Raudenbush, and F. Earls, “Neighborhoods and violent crime: A multilevel study of collective efficacy,” Science, vol. 277, no. 5328, pp. 918–924, 1997. [Online]. Available: http://dx.doi.org/10.1126/science.277.5328.918 107, 109, 118, 121, 123
[6] R. D. Putnam, R. Leonardi, and R. Y. Nanetti, Making democracy work: Civic traditions in modern Italy. Princeton University Press, 1994. 107
[7] G. Kessler, M. Luzzi, and Others, Sociología del delito amateur. Paidós, 2004. 107, 121, 123
[8] J. G. Rivera-González, “El deterioro del Capital Social como promotor de la violencia y la delincuencia entre la población del municipio de Rioverde, San Luis Potosí,” Papeles de Población, vol. 22, no. 87, 2016. 107
[9] A. Gaviria, “Increasing returns and the evolution of violent crime: the case of Colombia,” Journal of development economics, vol. 61, no. 1, pp. 1–25, 2000. 107, 108
[10] R. I. Mawby, “Exploring the relationship between crime and place in the countryside,” Journal of Rural Studies, vol. 39, pp. 262–270, 2015. [Online]. Available: http://dx.doi.org/10.1016/j.jrurstud.2014.12.003 107, 120
[11] P. Rocke, Sociological theories of crime, M. Mike, M. Rod, and R. Robert, Eds. Oxford University Press, 2002. 108, 112, 117
[12] D. Cárdenas, D. Lorduy, and C. Velásquez, Sicariato en Bogotá: emergencia y desarrollo de una modalidad homicida en la ciudad. Una aproximación cualitativa y exploratoria. Forensis 2009. Datos para la vida. Bogotá: Instituto Nacional de Medicina Legal y Ciencias Forenses. En imprenta, 2009, vol. 11, no. 1. [Online]. Available: https://goo.gl/MWOdxf 108, 117
[13] N. Malleson, “Using Agent-Based Models to Simulate Crime,” Springer, pp. 411–434, 2012. [Online]. Available: http://dx.doi.org/10.1007/978-90-481-8927-4_19 108, 123
[14] C. Urban and B. Schmidt, “PECS-Agent-Based Modelling of Human Behaviour,” in AAAI Technical Report FS-01-02. AAAI, 2001, p. 6. 108, 112, 113, 114
[15] C. R. Browning and K. A. Cagney, “Neighborhood structural disadvantage, collective efficacy, and self-rated physical health in an urban setting,” Journal of health and social behavior, vol. 43, no. 4, pp. 383–399, 2002. [Online]. Available: http://www.jstor.org/stable/3090233 109
[16] N. Comstock, L. M. Dickinson, J. A. Marshall, M.-J. Soobader, M. S. Turbin, M. Buchenau, and J. S. Litt, “Neighborhood attachment and its correlates: Exploring neighborhood conditions, collective efficacy, and gardening,” Journal of Environmental Psychology, vol. 30, no. 4, pp. 435–442, 2010. 109, 123
[17] J. A. Schafer, B. M. Huebner, and T. S. Bynum, “Fear of crime and criminal victimization: Gender-based contrasts,” Journal of Criminal Justice, vol. 34, no. 3, pp. 285–301, 2006. [Online]. Available: http://dx.doi.org/10.1016/j.jcrimjus.2006.03.003 109
[18] M. H. Marzbali, A. Abdullah, N. A. Razak, and M. J. M. Tilaki, “Examining social cohesion and victimization in a Malaysian multiethnic neighborhood,” International Journal of Law, Crime and Justice, vol. 42, no. 4, pp. 384–405, 2014. [Online]. Available: http://dx.doi.org/10.1016/j.ijlcj.2014.03.001 109
[19] S. D. Johnson and K. J. Bowers, “Permeability and burglary risk: are cul-desacs safer?” Journal of Quantitative Criminology, vol. 26, no. 1, pp. 89–111, 2010. 109
[20] J. Scott, Social network analysis. London: Sage, 2012. 109
[21] M. 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. [Online]. Available: http://dx.doi.org/10.1146/annurev.soc.27.1.415 109
[22] K. J. Robinson, “The Rise of Choice in the US University and College: 1910- 20051,” in Sociological forum, vol. 26, no. 3. Wiley Online Library, 2011, pp. 601–622. [Online]. Available: http://www.jstor.org/stable/23027302 109
[23] S. Meyer and L. Mazerolle, “Family Engagement Strategies to Reduce Crime,” in Encyclopedia of Criminology and Criminal Justice. Springer, 2014, pp. 1563–1573. 110, 111, 118, 121, 123
[24] A. A. Braga, D. M. Kennedy, E. J. Waring, and A. M. Piehl, “Problem-oriented policing, deterrence, and youth violence: An evaluation of Boston’s Operation Ceasefire,” Journal of Research in Crime and Delinquency, vol. 38, no. 3, pp. 195–225, 2001. [Online]. Available: http://dx.doi.org/10.1177/0022427801038003001 110
[25] L. W. Sherman, J. D. Schmidt, and D. P. Rogan, Policing domestic violence: Experiments and dilemmas. Free Press, 1992. 110
[26] D. J. Watts and S. H. Strogatz, “Collective dynamics of small-world networks,” Nature, vol. 393, no. 6684, pp. 440–442, 1998. [Online]. Available: http://dx.doi.org/10.1038/30918 111, 112
[27] R. Monasson, “Diffusion, localization and dispersion relations on small-world lattices,” The European Physical Journal B-Condensed Matter and Complex Systems, vol. 12, no. 4, pp. 555–567, 1999. 111, 112
[28] M. Newman and D. Watts, “Renormalization group analysis of the smallword network model,” Physics Letters A, vol. 12, no. 4, pp. 555–567, 1999. [Online]. Available: http://dx.doi.org/10.1016/S0375-9601(99)00757-4 111
[29] R. Plutchik, The psychology and biology of emotion. HarperCollins College Publishers, 1994. 114
[30] F. Toates, “Cognition, motivation, emotion and action: a dynamic and vulnerable interdependence,” Applied Animal Behaviour Science, vol. 86, no. 3, pp. 173–204, 2004. [Online]. Available: http://dx.doi.org/10.1016/j.applanim.2004.02.010 114
[31] W. G. Jiménez-García, “Hacia una tipología de lugares peligrosos. Caso de estudio de la comuna 11 de Dosquebradas, Colombia,” Revista Criminalidad, vol. 56, no. 1, pp. 133–156, 2014. 121