Usporedite metode

	Analiza usmjerenih društvenih mreža	Usmjereno otkrivanje zajednica
Područje	Analiza mreža	Analiza mreža
Obitelj	Machine learning	Machine learning
Godina nastanka	1994	2008
Tvorac	Wasserman, S. & Faust, K.	Leicht, E. A. & Newman, M. E. J.; Rosvall, M. & Bergstrom, C. T.
Vrsta	Structural analysis of directed graphs	Graph partitioning / modularity optimization
Temeljni izvor	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.
Drugi nazivi	directed SNA, digraph analysis, directed graph network analysis, asymmetric network analysis	directed graph clustering, community detection in digraphs, directed modularity optimization, directed network partitioning
Srodne	5	6
Sažetak	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.