Сравнение на методи

	Анализ на насочени двумодални мрежи	Анализ на насочена модуларност
Област	Мрежови анализ	Мрежови анализ
Семейство	Machine learning	Machine learning
Година на възникване	1997	2008
Създател	Borgatti, S. P. & Everett, M. G.	Leicht, E. A. & Newman, M. E. J.
Тип	Structural network analysis	Community detection / graph partitioning
Основополагащ източник	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.
Други названия	directed bipartite network analysis, asymmetric affiliation network analysis, directed actor-event network analysis, directed two-mode graph analysis	directed community detection via modularity, directed Q-modularity, digraph modularity optimization, Leicht-Newman modularity
Свързани	6	5
Резюме	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 modularity analysis extends the classic Newman-Girvan modularity framework to directed graphs, where edges carry a source and a destination. Formalized by Leicht and Newman in 2008, it partitions nodes into communities by maximizing a modularity score that accounts for each node's separate in-degree and out-degree in the null model, making it the standard approach for community detection in citation networks, information flows, and other asymmetric relational data.