2023/06/08 by Rémy Cazabet, Cazabet, Remy, Salvatore Citraro +3
Computer Science · Physics and Astronomy · #Complex Network Analysis Techniques #FOS: Computer and information sciences #Opportunistic and Delay-Tolerant Networks #Peer-to-Peer Network Technologies #Social and Information Networks (cs.SI)
paper · pdf · doi:10.48550/arxiv.2306.05274
openalex publication_date 2023/06/08 · openalex created_date 2023/06/10 · openalex updated_date 2026/08/03
Network structure is often considered one of the most important features of a network, and various models exist to generate graphs having one of the most studied types of structures, such as blocks/communities or spatial structures. In this article, we introduce a framework for the generation of random graphs with a controlled size -- number of nodes, edges -- and a customizable structure, beyond blocks and spatial ones, based on node-pair rank and a tunable probability function allowing to control the amount of randomness. We introduce a structure zoo -- a collection of original network structures -- and conduct experiments on the small-world properties of networks generated by those structures. Finally, we introduce an implementation as a Python library named Structify-net.