Порівняння методів

	Спрямований двомодовий аналіз мереж	Виявлення спрямованих спільнот
Галузь	Мережевий аналіз	Мережевий аналіз
Родина	Machine learning	Machine learning
Рік появи	1997	2008
Автор методу	Borgatti, S. P. & Everett, M. G.	Leicht, E. A. & Newman, M. E. J.; Rosvall, M. & Bergstrom, C. T.
Тип	Structural network analysis	Graph partitioning / modularity optimization
Основоположне джерело	Wasserman, S. & Faust, K. (1994). Social Network Analysis: Methods and Applications (Ch. 8). 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.
Інші назви	directed bipartite network analysis, asymmetric affiliation network analysis, directed actor-event network analysis, directed two-mode graph analysis	directed graph clustering, community detection in digraphs, directed modularity optimization, directed network partitioning
Пов'язані	6	6
Підсумок	Directed two-mode network analysis studies bipartite graphs in which nodes belong to two distinct sets — such as actors and events, authors and papers, or firms and markets — and edges carry a direction, capturing asymmetric relationships like citation, referral, or endorsement. Combining the duality of two-mode structure with directed tie semantics reveals flow patterns and influence asymmetries that undirected or single-mode analyses would miss.	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.