Identifying influential node groups in networks with core-periphery structure
Gyuho Bae, Philip A. Knight, and Young-Ho Eom

TL;DR
This paper investigates the structural conditions under which core nodes in networks with core-periphery structure become influential, focusing on internal and external connectivity patterns and their impact on influence distribution.
Contribution
It identifies the role of internal and external core connectivity in determining node influence, providing a structural criterion for influential cores in networks.
Findings
Internal core connectivity correlates positively with influence.
External core connectivity influences influence up to a threshold.
Model networks confirm real-world observations.
Abstract
Identifying influential spreaders is a crucial problem for practical applications in network science. The core-periphery(C-P) structure, common in many real-world networks, comprises a densely interconnected group of nodes(core) and the rest of the sparsely connected nodes subordinated to the core(periphery). Core nodes are expected to be more influential than periphery nodes generally, but recent studies suggest that this is not the case in some networks. In this work, we look for mesostructural conditions that arise when core nodes are significantly more influential than periphery nodes. In particular, we investigate the roles of the internal and external connectivity of cores in their relative influence. We observe that the internal and external connectivity of cores are broadly distributed, and the relative influence of the cores is also broadly distributed in real-world networks.…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsComplex Network Analysis Techniques · Graph theory and applications
