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The Inverse Contagion Problem (ICP) vs

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  • Mushkin, I.
  • Solomon, S.

Abstract

We study the inverse contagion problem (ICP). As opposed to the direct contagion problem, in which the network structure is known and the question is when each node will be contaminated, in the inverse problem the links of the network are unknown but a sequence of contagion histories (the times when each node was contaminated) is observed. We consider two versions of the ICP: The strong problem (SICP), which is the reconstruction of the network and has been studied before, and the weak problem (WICP), which requires “only” the prediction (at each time step) of the nodes that will be contaminated at the next time step (this is often the real life situation in which a contagion is observed and predictions are made in real time). Moreover, our focus is on analyzing the increasing accuracy of the solution, as a function of the number of contagion histories already observed. For simplicity, we discuss the simplest (deterministic and synchronous) contagion dynamics and the simplest solution algorithm, which we have applied to different network types.

Suggested Citation

  • Mushkin, I. & Solomon, S., 2017. "The Inverse Contagion Problem (ICP) vs," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 484(C), pages 516-531.
    • Handle: RePEc:eee:phsmap:v:484:y:2017:i:c:p:516-531
    DOI: 10.1016/j.physa.2017.04.110
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    References listed on IDEAS

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