2012/07/13 by Günce Keziban Orman, Keziban Orman, Vincent Labatut +1
Computer Science · Physics and Astronomy · #Cluster analysis #Community structure #Complex Network Analysis Techniques #Distribution (mathematics) #Empirical research #Opportunistic and Delay-Tolerant Networks #Peer-to-Peer Network Technologies #Property (philosophy) #Relation (database) #Transitive relation #Zero (linguistics) #cs.SI #physics.soc-ph
paper · pdf · doi:10.1007/978-3-642-30287-9_11
published as Studies in Computational Intelligence, 424:99-110, 2013 · 3rd Workshop on Complex Networks, Melbourne, Florida : United States (2012)
arxiv created 2012/07/13 · openalex publication_date 2012/07/26 · arxiv updated 2012/08/16 · openalex created_date 2016/06/24 · openalex updated_date 2026/08/05
One of the most prominent properties in real-world networks is the presence of a community structure, i.e. dense and loosely interconnected groups of nodes called communities. In an attempt to better understand this concept, we study the relationship between the strength of the community structure and the network transitivity (or clustering coefficient). Although intuitively appealing, this analysis was not performed before. We adopt an approach based on random models to empirically study how one property varies depending on the other. It turns out the transitivity increases with the community structure strength, and is also affected by the distribution of the community sizes. Furthermore, increasing the transitivity also results in a stronger community structure. More surprisingly, if a very weak community structure causes almost zero transitivity, the opposite is not true and a network with a close to zero transitivity can still have a clearly defined community structure. Further analytical work is necessary to characterize the exact nature of the identified relationship.