Linganisha mbinu

	Mwanamitindo wa Mfumo wa Mfumo wa Mitandao ya Kielelezo ya Kuelekezwa	Ugunduzi wa Jumuiya Zinazoongozwa
Nyanja	Uchanganuzi wa Mitandao	Uchanganuzi wa Mitandao
Familia	Machine learning	Machine learning
Mwaka wa asili	1986 (foundations); 2007 (modern directed ERGM formulation)	2008
Mwanzilishi	Frank, O. & Strauss, D.; extended by Robins, Pattison, Kalish & Lusher	Leicht, E. A. & Newman, M. E. J.; Rosvall, M. & Bergstrom, C. T.
Aina	Statistical generative model for directed networks	Graph partitioning / modularity optimization
Chanzo asilia	Robins, G., Pattison, P., Kalish, Y. & Lusher, D. (2007). An introduction to exponential random graph (p*) models for social networks. Social Networks, 29(2), 173-191.	Leicht, E. A. & Newman, M. E. J. (2008). Community structure in directed networks. Physical Review Letters, 100(11), 118703.
Majina mbadala	Directed ERGM, p-star model (directed), directed p* model, directed Markov graph model	directed graph clustering, community detection in digraphs, directed modularity optimization, directed network partitioning
Zinazohusiana	4	6
Muhtasari	The Directed Exponential Random Graph Model (Directed ERGM) is a family of statistical models for directed networks that estimates the probability of observing a given directed graph as a function of structural configurations — such as reciprocity, transitive triads, and in-degree centralization — and node or dyad covariates, enabling principled inference about the social processes that generate directed ties.	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.