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Can I read Targeted Influence Maximization in Complex Networks on EtoBox?
Targeted Influence Maximization in Complex Networks by Renquan Zhang; Xiaolin Wang; Sen Pei is a Physics and Astronomy article available to read on EtoBox.
What is Targeted Influence Maximization in Complex Networks about?
Many real-world applications based on spreading processes in complex networks aim to deliver information to specific target nodes. However, it remains challenging to optimally select a set of spreaders to initiate the spreading process. In this paper, we study the targeted influence maximization problem using a susceptible–infected–recovered (SIR) model as an example. Formulated as a combinatorial optimization, the objective is to identify a given number of spreaders that can maximize the influence over target nodes while minimize the influence over non-target nodes. To find a practical solution to this optimization problem, we develop a theoretical framework based on a message passing process and perform a stability analysis on the equilibrium solution using non-backtracking (NB) matrices. Based on the optimal perturbation on the equilibrium solution, we further introduce a metric, termed targeted collective influence, for each node to identify influential spreaders for targeted spreading processes. The proposed method, validated in both synthetic and real-world networks, outperforms other competing heuristic approaches. Our results provide a framework for analyzing the targeted i
Who reads Targeted Influence Maximization in Complex Networks?
It is typically read by researchers, students, and practitioners in Physics and Astronomy.
- Author
- Renquan Zhang; Xiaolin Wang; Sen Pei
- Publisher
- Elsevier BV
- Published
- 2023
- Language
- EN
- Field
- Physics and Astronomy (Physical Sciences)