Сравнение методов

	Взвешенный анализ мо-дулярности	Взвешенный анализ социальных сетей
Область	Сетевой анализ	Сетевой анализ
Семейство	Machine learning	Machine learning
Год появления	2004	2004–2010
Автор метода	Newman, M. E. J.	Barrat, A.; Opsahl, T. et al.
Тип	Community structure optimization on weighted graphs	Network analysis framework
Основополагающий источник	Newman, M. E. J. (2004). Analysis of weighted networks. Physical Review E, 70(5), 056131.	Barrat, A., Barthélemy, M., Pastor-Satorras, R., & Vespignani, A. (2004). The architecture of complex weighted networks. Proceedings of the National Academy of Sciences, 101(11), 3747–3752.
Другие названия	weighted modularity, weighted Q optimization, weighted network community detection, strength-based modularity	Weighted SNA, valued network analysis, tie-strength network analysis, weighted graph analysis
Связанные	5	6
Сводка	Weighted modularity analysis extends the classical Newman-Girvan modularity measure to networks where edges carry numeric strengths (frequencies, intensities, costs). By replacing binary adjacency with tie weights, it finds community partitions that reflect how densely interconnected subgroups are relative to what is expected under a weighted null model, yielding more nuanced groupings than unweighted approaches on data where edge strength varies meaningfully.	Weighted Social Network Analysis extends classical SNA by assigning numeric values — weights — to ties between actors, capturing tie strength, interaction frequency, or resource flow. Rather than treating all connections as equal, it reveals who holds privileged positions by virtue of the intensity, not merely the existence, of their relationships.