2012/02/29 by Qian-Ming Zhang, Linyuan Lü, Wenqiang Wang +4 · 131 citations
Biochemistry, Genetics and Molecular Biology · Computer Science · Mathematics · Physics and Astronomy · Psychology · #Algorithm #Artificial intelligence #Bioinformatics and Genomic Networks #Cluster analysis #Combinatorics #Community structure #Complex Network Analysis Techniques #Complex network #Computer network #Computer science #Directed graph #Homophily #Link (geometry) #Mathematics #Mechanism (biology) #Mental Health Research Topics #Network analysis #Network theory #Physics #Theoretical computer science #cs.IR #cs.SI #physics.data-an #physics.soc-ph
paper · pdf · doi:10.1371/journal.pone.0055437
published in PLoS ONE 8(2), e55437 (Public Library of Science) · 8 pages, 6 figures
openalex publication_date 2013/02/11 · arxiv created 2013/07/31 · arxiv updated 2013/08/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
Uncovering factors underlying the network formation is a long-standing challenge for data mining and network analysis. In particular, the microscopic organizing principles of directed networks are less understood than those of undirected networks. This article proposes a hypothesis named potential theory, which assumes that every directed link corresponds to a decrease of a unit potential and subgraphs with definable potential values for all nodes are preferred. Combining the potential theory with the clustering and homophily mechanisms, it is deduced that the Bi-fan structure consisting of 4 nodes and 4 directed links is the most favored local structure in directed networks. Our hypothesis receives strongly positive supports from extensive experiments on 15 directed networks drawn from disparate fields, as indicated by the most accurate and robust performance of Bi-fan predictor within the link prediction framework. In summary, our main contribution is twofold: (i) We propose a new mechanism for the local organization of directed networks; (ii) We design the corresponding link prediction algorithm, which can not only testify our hypothesis, but also find out direct applications in missing link prediction and friendship recommendation.