Abstract
Network-Oriented Modeling has successfully been applied to obtain network models for a wide range of phenomena, including Biological Networks, Mental Networks, and Social Networks. In this paper it is discussed how the interpretation of a network as a causal network and taking into account dynamics in the form of temporal-causal networks, brings more depth. The basics and the scope of applicability of such a Network-Oriented Modelling approach are discussed and illustrated. This covers, for example, Social Network models for social contagion or information diffusion, adaptive Mental Network models for Hebbian learning and adaptive Social Network models for evolving relationships. From the more fundamental side, it will be discussed how emerging network behavior can be related to network structure.
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Treur, J. (2019). The Ins and Outs of Network-Oriented Modeling: From Biological Networks and Mental Networks to Social Networks and Beyond. In: Nguyen, N., Kowalczyk, R., Hernes, M. (eds) Transactions on Computational Collective Intelligence XXXII. Lecture Notes in Computer Science(), vol 11370. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-58611-2_2
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