Comparar métodos

	Análise de Difusão em Redes Temporais	Análise Temporal de Redes Sociais
Área	Análise de redes	Análise de redes
Família	Machine learning	Machine learning
Ano de origem	2012	2000s–2010s
Autor original	Holme, P. & Saramäki, J.	Moody, J.; Holme, P.; Saramäki, J.
Tipo	Network analysis framework	Longitudinal network analysis
Fonte seminal	Holme, P. & Saramäki, J. (2012). Temporal networks. Physics Reports, 519(3), 97–125.	Holme, P., & Saramäki, J. (2012). Temporal networks. Physics Reports, 519(3), 97–125.
Outros nomes	TNDA, dynamic network diffusion, time-varying network spreading, diffusion on temporal networks	TSNA, longitudinal social network analysis, time-varying network analysis, dynamic SNA
Relacionados	5	4
Resumo	Temporal Network Diffusion Analysis studies how information, disease, influence, or other contagions spread through networks whose structure changes over time. By modeling edges as time-stamped contacts rather than static links, it captures the critical role of timing and ordering in determining which nodes get reached, how fast, and through which pathways — producing conclusions that static network models systematically miss.	Temporal 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.