Identify multiple seeds for influence maximization by statistical physics approach and multi-hop coverage

Finding the influential vertexes as seeds in a real network is an important problem which relates to wide applications. However, some conventional heuristic methods do not consider the overlap phenomenon. In order to avoid the overlap of spreading, we propose a new method in combing the statistical...

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Bibliographic Details
Published inApplied network science Vol. 7; no. 1; pp. 1 - 16
Main Authors Liao, Fuxuan, Hayashi, Yukio
Format Journal Article
LanguageEnglish
Published Cham Springer International Publishing 25.07.2022
Springer Nature B.V
SpringerOpen
Subjects
Complexity
Computer Appl. in Social and Behavioral Sciences
Computer Science
Computer simulation
Heuristic
Heuristic methods
Influence maximum problem
L-hop coverage
Methods
Multiple seeds
Overlapping phenomena
Propagation
Science
Seeds
Simulation and Modeling
SIR model
Social networks
Statistical physics
Vertex cover problem
Influence maximum problem
SIR model
Overlapping phenomena
Statistical physics approach
L-hop coverage
Vertex cover problem
Multiple seeds
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Summary:Finding the influential vertexes as seeds in a real network is an important problem which relates to wide applications. However, some conventional heuristic methods do not consider the overlap phenomenon. In order to avoid the overlap of spreading, we propose a new method in combing the statistical physics approach and multi-hop coverage. We also propose a faster epidemic model which does not need the averaging of stochastic behavior. Through the computer simulation, the obtained results show that our method can outperforms other conventional methods in the meaning of stronger spreading power per seed.
ISSN:2364-8228
2364-8228
DOI:10.1007/s41109-022-00491-x