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A computational framework for understanding risk factors in cybercrime

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Autor
Pérez Sánchez, Jaime
Awad, Edmond
Castro Ponce, Mario
López López, Gregorio
Bueno Guerra, Nereida
Reneses Botija, María
Riberas Gutiérrez, María
Gómez Dorado, Aarón
Estado
info:eu-repo/semantics/draft
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Resumen
 
 
In this paper, we present a prototype computational framework to study the risk factors that play a relevant role in cybercrime. Intending to address the limitations of the classical approaches used in social science and the black box approaches commonly used in computational science, we propose an iterative study process that moves the focus towards the use of causal and Bayesian methodologies to obtain a better complete picture of these complex processes and guide the design of new experiments. In this paper, to exemplify our proposal, we also analyze data from a survey of Spanish children about their cyberbullying-related experiences and various personal, environmental, and technological factors that could play a key role in online victimization. The results of our study bring together approaches from social and computer science, highlighting the need for multidisciplinary studies to understand better the complex human process behind cybercrime.
 
URI
http://hdl.handle.net/11531/87344
A computational framework for understanding risk factors in cybercrime
Palabras Clave

Online Victimization; Adolescents; Cyberbullying; Causality; Bayesian Statistics
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Repositorio de la Universidad Pontificia Comillas copyright © 2015  Desarrollado con DSpace Software
Contacto | Sugerencias