Machine learningNetwork science
Directed Social Network Analysis
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.
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Sources
- Wasserman, S. & Faust, K. (1994). Social Network Analysis: Methods and Applications. Cambridge University Press. ISBN: 978-0-521-38707-1
- Newman, M. E. J. (2010). Networks: An Introduction. Oxford University Press. ISBN: 978-0-19-920665-0
Related methods
Referenced by
Directed Betweenness CentralityDirected Closeness CentralityDirected Community DetectionDirected Ego Network AnalysisDirected Eigenvector CentralityDirected Exponential Random Graph ModelDirected Knowledge Graph AnalysisDirected Modularity AnalysisDirected Multiplex Network AnalysisDirected PageRankDirected Two-Mode Network Analysis