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Řízené detekce komunit×Sociální síťová analýza×
OborAnalýza sítíAnalýza sítí
RodinaMachine learningMachine learning
Rok vzniku20081934 (sociometry); 1994 (modern formalization)
TvůrceLeicht, E. A. & Newman, M. E. J.; Rosvall, M. & Bergstrom, C. T.Moreno, J.L.; formalized by Wasserman & Faust
TypGraph partitioning / modularity optimizationStructural/relational analysis framework
Původní zdrojLeicht, E. A. & Newman, M. E. J. (2008). Community structure in directed networks. Physical Review Letters, 100(11), 118703. DOI ↗Wasserman, S. & Faust, K. (1994). Social Network Analysis: Methods and Applications. Cambridge University Press. ISBN: 978-0-521-38707-1
Další názvydirected graph clustering, community detection in digraphs, directed modularity optimization, directed network partitioningSNA, network analysis, sociometric analysis, relational analysis
Příbuzné65
ShrnutíDirected community detection identifies densely interconnected groups of nodes in a directed network, accounting for the asymmetry of edges (e.g., A follows B does not imply B follows A). Adapting modularity or flow-based criteria to directed graphs reveals clusters that undirected methods systematically miss, making it essential for citation networks, follower graphs, and biological regulatory pathways.Social Network Analysis (SNA) is a structural method that maps and measures relationships and flows between people, groups, organizations, or other entities modeled as nodes connected by ties (edges). Rather than focusing on individual attributes, SNA reveals how the pattern of connections shapes behavior, influence, information flow, and outcomes within a system.
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ScholarGatePorovnat metody: Directed Community Detection · Social Network Analysis. Získáno 2026-06-18 z https://scholargate.app/cs/compare