방법 비교

	가중치 시계열 네트워크 분석	가중치 사회 연결망 분석 (Weighted Social Network Analysis)
분야	네트워크 분석	네트워크 분석
계열	Machine learning	Machine learning
기원 연도	2004–2012	2004–2010
창시자	Holme, P. & Saramaki, J. (temporal networks); Barrat et al. (weighted networks)	Barrat, A.; Opsahl, T. et al.
유형	Network analysis technique	Network analysis framework
원전	Holme, P. & Saramaki, J. (2012). Temporal networks. Physics Reports, 519(3), 97–125.	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.
별칭	WTNA, weighted time-varying network analysis, weighted dynamic network analysis, weighted evolving network analysis	Weighted SNA, valued network analysis, tie-strength network analysis, weighted graph analysis
관련	6	6
요약	Weighted temporal network analysis studies networks whose edges carry numerical weights — representing interaction strength, frequency, or intensity — and whose structure changes over time. It combines the time-varying perspective of temporal network analysis with the quantitative precision of weighted graph metrics, revealing not only when connections exist but how strong they are at each moment.	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.