Abstract
In this paper we present the application of a novel methodology to scientific citation and collaboration networks. This methodology is designed for understanding the governing dynamics of evolving networks and relies on an attachment kernel, a scalar function of node properties, that stochastically drives the addition and deletion of vertices and edges. We illustrate how the kernel function of a given network can be extracted from the history of the network and discuss other possible applications.
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Csárdi, G., Strandburg, K., Zalányi, L., Tobochnik, J., érdi, P. (2010). Estimating the dynamics of kernel-based evolving networks. In: Minai, A., Braha, D., Bar-Yam, Y. (eds) Unifying Themes in Complex Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85081-6_12
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DOI: https://doi.org/10.1007/978-3-540-85081-6_12
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-85080-9
Online ISBN: 978-3-540-85081-6
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