On the influence maximization problem and the percolation phase transition

Yoav Kolumbus and Sorin Solomon

Physica A: Statistical Mechanics and its Applications, 2021, vol. 573, issue C

Abstract: We analyze the problem of network influence maximization in the uniform independent cascade model: Given a network with N nodes and a probability p for a node to contaminate a neighbor, find a set of k initially contaminated nodes that maximizes the expected number of eventually contaminated nodes. This problem is of interest theoretically and for many applications in social networks. Unfortunately, it is a NP-hard problem. Using Percolation Theory, we show that in practice the problem is hard only in a vanishing neighborhood of a critical value p=pc. For p>pc there exists a “Giant Cluster” of order N, that is easily found in finite time. For pKeywords: Networks; Influence maximization; Percolation; Empirical hardness (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:573:y:2021:i:c:s0378437121002004

DOI: 10.1016/j.physa.2021.125928

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