Identifying vital nodes for influence maximization in attributed networks.

ABSTRACT: Identifying a set of vital nodes to achieve influence maximization is a topic of general interest in network science. Many algorithms have been proposed to solve the influence maximization problem in complex networks. Most of them just use topology information of networks to measure the node influence. However, the node attribute is also an important factor for measuring node influence in attributed networks. To tackle this problem, we first propose an extension model of linear threshold (LT) propagation model to simulate the information propagation in attributed networks. Then, we propose a novel community-based method to identify a set of vital nodes for influence maximization in attributed networks. The proposed method considers both topology influence and attribute influence of nodes,

SUBMITTER: Wang Y 

PROVIDER: S-EPMC9805466 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature