手法を比較

	指向性ソーシャルネットワーク分析	有向コミュニティ検出
分野	ネットワーク分析	ネットワーク分析
系統	Machine learning	Machine learning
提唱年	1994	2008
提唱者	Wasserman, S. & Faust, K.	Leicht, E. A. & Newman, M. E. J.; Rosvall, M. & Bergstrom, C. T.
種類	Structural analysis of directed graphs	Graph partitioning / modularity optimization
原典	Wasserman, S. & Faust, K. (1994). Social Network Analysis: Methods and Applications. Cambridge University Press. ISBN: 978-0-521-38707-1	Leicht, E. A. & Newman, M. E. J. (2008). Community structure in directed networks. Physical Review Letters, 100(11), 118703.
別名	directed SNA, digraph analysis, directed graph network analysis, asymmetric network analysis	directed graph clustering, community detection in digraphs, directed modularity optimization, directed network partitioning
関連	5	6
概要	Directed Social Network Analysis (directed SNA) studies networks in which every tie has an explicit direction — from a sender to a receiver — rather than treating relationships as symmetric. It extends the classical SNA toolkit with in-degree, out-degree, reciprocity, and asymmetric path measures, making it the appropriate framework wherever relationship direction carries substantive meaning, such as citation flows, advice-seeking, follower graphs, or information cascades.	Directed 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.