Linganisha mbinu

	Uchambuzi wa Mitandao ya Kijamii Iliyoongozwa	Ugunduzi wa Jumuiya Zinazoongozwa
Nyanja	Uchanganuzi wa Mitandao	Uchanganuzi wa Mitandao
Familia	Machine learning	Machine learning
Mwaka wa asili	1994	2008
Mwanzilishi	Wasserman, S. & Faust, K.	Leicht, E. A. & Newman, M. E. J.; Rosvall, M. & Bergstrom, C. T.
Aina	Structural analysis of directed graphs	Graph partitioning / modularity optimization
Chanzo asilia	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.
Majina mbadala	directed SNA, digraph analysis, directed graph network analysis, asymmetric network analysis	directed graph clustering, community detection in digraphs, directed modularity optimization, directed network partitioning
Zinazohusiana	5	6
Muhtasari	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.