2014/05/31 by Hang-Hyun Jo, Young-Ho Eom
Computer Science · Mathematics · Physics and Astronomy · Psychology · Social Sciences · #Combinatorics #Complex Network Analysis Techniques #Complex network #Computer science #Correlation #Degree (music) #Evolutionary Game Theory and Cooperation #Friendship #Mathematics #Node (physics) #Opinion Dynamics and Social Influence #Physics #Psychology #Relevance (law) #Social psychology #Statistical physics #Statistics #Theoretical computer science #Topology (electrical circuits) #Uncorrelated #cs.SI #physics.soc-ph
paper · pdf · doi:10.1103/physreve.90.022809
published as Phys. Rev. E 90, 022809 (2014) · 7 pages, 5 figures
arxiv created 2014/07/10 · openalex publication_date 2014/08/21 · arxiv updated 2014/08/26 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
One of the interesting phenomena due to topological heterogeneities in complex networks is the friendship paradox: Your friends have on average more friends than you do. Recently, this paradox has been generalized for arbitrary node attributes, called the generalized friendship paradox (GFP). The origin of GFP at the network level has been shown to be rooted in positive correlations between degrees and attributes. However, how the GFP holds for individual nodes needs to be understood in more detail. For this, we first analyze a solvable model to characterize the paradox holding probability of nodes for the uncorrelated case. Then we numerically study the correlated model of networks with tunable degree-degree and degree-attribute correlations. In contrast to the network level, we find at the individual level that the relevance of degree-attribute correlation to the paradox holding probability may depend on whether the network is assortative or dissortative. These findings help us to understand the interplay between topological structure and node attributes in complex networks.