Previous research on information propagation has primarily focused on either online social
networks or offline social networks. Additionally, there remains a gap in understanding the …

The study of influential spreaders has become a growing area of interest within network
sciences due to its critical implications in understanding the robustness and vulnerability of …

How to accurately identify influential nodes in complex networks remains a challenge due to
the increasing network scale, complex topology, and dynamic network behaviors. Although …

One key challenge within the domain of network science is accurately finding important
nodes within a network. In recent years, researchers have proposed various node centrality …

Identifying nodes that hold relative importance in complex networks is a burgeoning
research area. Previous studies have demonstrated the effectiveness of the gravity model in …

How to identify important nodes in multi-layer networks is still an unresolved issue in
network science, which has aroused the interest of many researchers. In addition, the …

Given the heterogeneity of real-world networks and the low efficiency of directly mining
networks, heterogeneous information network (HIN) representation learning, which learns …

Influencers in complex social networks are crucial for shaping the dynamics of information
dissemination, viral marketing strategies, and controlling public opinion. This raises an …

The study of complex networks is increasingly attracting widespread attention, and the
importance analysis of key nodes with significant influence has always been a core problem …

Measuring the centrality of nodes in a network is a vital and significant task in analyzing the
influence of nodes and information dissemination. Existing methods measure the centrality …