Сравнение на методи

	Динамичен анализ на его-мрежи	Анализ на времеви мрежи
Област	Мрежови анализ	Мрежови анализ
Семейство	Machine learning	Process / pipeline
Година на възникване	1990s–2015	2012
Създател	Burt, R. S.; Wellman, B. (foundational ego-net); dynamic extension developed across the 1990s–2010s	Holme & Saramäki (2012) — seminal framework
Тип	Longitudinal network analysis framework	Dynamic graph analysis
Основополагащ източник	Burt, R. S. (1992). Structural Holes: The Social Structure of Competition. Harvard University Press. ISBN: 978-0-674-84372-1	Holme, P. & Saramäki, J. (2012). Temporal Networks. Physics Reports, 519(3), 97-125.
Други названия	longitudinal ego network analysis, temporal ego network analysis, personal network dynamics, dynamic personal network analysis	dynamic network analysis, time-varying network analysis, Zamansal Ağ Analizi (Temporal / Dynamic Networks)
Свързани	3	3
Резюме	Dynamic ego network analysis examines how the personal network surrounding a focal individual (the ego) changes over time. By collecting the same ego-centered network data at multiple time points, researchers can track tie formation and dissolution, shifts in network composition, and changes in structural properties such as density, constraint, and network size — and link these dynamics to individual outcomes.	Temporal network analysis, formalised by Holme and Saramäki in their landmark 2012 Physics Reports survey, is the study of networks in which edges appear and disappear over time. Rather than collapsing all contacts into a single static graph, the approach preserves the precise timing of interactions — whether as contact sequences, time-stamped event lists, or windowed snapshots — and uses that timing to track how influence, disease, or information can actually propagate through the system.