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Temporal Social Network Analysis×Temporal Community Detection×
ÄmnesområdeNätverksanalysNätverksanalys
FamiljMachine learningMachine learning
Ursprungsår2000s–2010s2010
UpphovspersonMoody, J.; Holme, P.; Saramäki, J.Mucha, P. J. et al.
TypLongitudinal network analysisNetwork clustering algorithm
UrsprungskällaHolme, P., & Saramäki, J. (2012). Temporal networks. Physics Reports, 519(3), 97–125. DOI ↗Mucha, P. J., Richardson, T., Macon, K., Porter, M. A., & Onnela, J.-P. (2010). Community structure in time-dependent, multiscale, and multiplex networks. Science, 328(5980), 876–878. DOI ↗
AliasTSNA, longitudinal social network analysis, time-varying network analysis, dynamic SNAdynamic community detection, time-varying community detection, evolutionary community detection, longitudinal community detection
Närliggande46
SammanfattningTemporal Social Network Analysis (TSNA) extends classic social network analysis by treating networks as time-varying structures. Rather than aggregating all ties into a single static snapshot, TSNA tracks when ties form, persist, and dissolve, enabling researchers to study how social structures evolve and how dynamic connectivity shapes diffusion, influence, and inequality over time.Temporal community detection identifies cohesive groups (communities) in networks whose structure changes over time. By treating each time snapshot as a network layer and coupling consecutive layers, it reveals how communities form, merge, split, grow, or dissolve — turning a sequence of static snapshots into a continuous narrative of group evolution.
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ScholarGateJämför metoder: Temporal Social Network Analysis · Temporal Community Detection. Hämtad 2026-06-18 från https://scholargate.app/sv/compare