# Ranking influential spreaders is an ill-defined problem

Tutkimustuotos: Lehtiartikkeli

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**Ranking influential spreaders is an ill-defined problem.** / Gu, Jain; Lee, Sungmin; Saramäki, Jari; Holme, Petter.

Tutkimustuotos: Lehtiartikkeli

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*EPL*, Vuosikerta. 118, Nro 6, 68002, Sivut 1-5. https://doi.org/10.1209/0295-5075/118/68002

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*EPL*,

*118*(6), 1-5. [68002]. https://doi.org/10.1209/0295-5075/118/68002

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### Bibtex - Lataa

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### RIS - Lataa

TY - JOUR

T1 - Ranking influential spreaders is an ill-defined problem

AU - Gu, Jain

AU - Lee, Sungmin

AU - Saramäki, Jari

AU - Holme, Petter

PY - 2017/6/1

Y1 - 2017/6/1

N2 - Finding influential spreaders of information and disease in networks is an important theoretical problem, and one of considerable recent interest. It has been almost exclusively formulated as a node-ranking problem - methods for identifying influential spreaders output a ranking of the nodes. In this work, we show that such a greedy heuristic does not necessarily work: the set of most influential nodes depends on the number of nodes in the set. Therefore, the set of n most important nodes to vaccinate does not need to have any node in common with the set of n + 1 most important nodes. We propose a method for quantifying the extent and impact of this phenomenon. By this method, we show that it is a common phenomenon in both empirical and model networks.

AB - Finding influential spreaders of information and disease in networks is an important theoretical problem, and one of considerable recent interest. It has been almost exclusively formulated as a node-ranking problem - methods for identifying influential spreaders output a ranking of the nodes. In this work, we show that such a greedy heuristic does not necessarily work: the set of most influential nodes depends on the number of nodes in the set. Therefore, the set of n most important nodes to vaccinate does not need to have any node in common with the set of n + 1 most important nodes. We propose a method for quantifying the extent and impact of this phenomenon. By this method, we show that it is a common phenomenon in both empirical and model networks.

UR - http://www.scopus.com/inward/record.url?scp=85028963257&partnerID=8YFLogxK

U2 - 10.1209/0295-5075/118/68002

DO - 10.1209/0295-5075/118/68002

M3 - Article

VL - 118

SP - 1

EP - 5

JO - EPL

JF - EPL

SN - 0295-5075

IS - 6

M1 - 68002

ER -

ID: 15307298