Abstract
The paper presents a recent development of an interdisciplinary research exploring innovative computational approaches to the scientific study of criminal behavior. The attention is focused on an attempt to combine social network analysis and agent-based modelling into CrimeMiner, an experimental framework that seamlessly integrates document-enhancement, visualization and network analysis techniques to support the study of criminal organizations. Our goal is both methodological and scientific. We are exploring how the synergy between ABM and SNA can support a deeper and more empirically grounded understanding of the complex dynamics taking place within criminal organizations between the individual/behavioral and social/structural level.
The authorship of this work can be attributed as follows: N. Lettieri (Sects. 1, 2.1, 2.2, 4, 4.2, 4.3 and 5); D. Malandrino and A. Altamura (Sects. 3.2, 4.1 and 4.2); V. Punzo (Sects. 2.3, 3.1 and 4.3).
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Lettieri, N., Altamura, A., Malandrino, D., Punzo, V. (2017). Agents Shaping Networks Shaping Agents: Integrating Social Network Analysis and Agent-Based Modeling in Computational Crime Research. In: Oliveira, E., Gama, J., Vale, Z., Lopes Cardoso, H. (eds) Progress in Artificial Intelligence. EPIA 2017. Lecture Notes in Computer Science(), vol 10423. Springer, Cham. https://doi.org/10.1007/978-3-319-65340-2_2
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