In this chapter, we review the classic susceptible-infected-recovered (SIR) model for disease spread as applied to a social network. In particular, we look at the problem of identifying nodes that are “spreaders” which cause a large part of the population to become infected under this model. To do so, we survey a variety of nodal measures based on centrality (degree, betweenness, etc.) and other methods (shell decomposition, nearest neighbor analysis, etc.). We then present a set of experiments that illustrate the relation of these nodal measures to spreading under the SIR model.
CITATION STYLE
Shakarian, P., Bhatnagar, A., Aleali, A., Shaabani, E., & Guo, R. (2015). The SIR model and identification of spreaders. In SpringerBriefs in Computer Science (Vol. 0, pp. 3–18). Springer. https://doi.org/10.1007/978-3-319-23105-1_2
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