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Detecção de Comunidades Ponderadas×Análise de Redes Sociais Ponderadas×
ÁreaAnálise de redesAnálise de redes
FamíliaMachine learningMachine learning
Ano de origem2004–20082004–2010
Autor originalNewman, M. E. J.; Blondel et al.Barrat, A.; Opsahl, T. et al.
TipoGraph clustering / community detectionNetwork analysis framework
Fonte seminalBlondel, V. D., Guillaume, J.-L., Lambiotte, R., & Lefebvre, E. (2008). Fast unfolding of communities in large networks. Journal of Statistical Mechanics: Theory and Experiment, 2008(10), P10008. DOI ↗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. DOI ↗
Outros nomesweighted graph clustering, community detection on weighted networks, weighted modularity optimization, WCDWeighted SNA, valued network analysis, tie-strength network analysis, weighted graph analysis
Relacionados66
ResumoWeighted community detection identifies densely connected groups — communities — in networks where edges carry numeric strengths (weights). By incorporating edge weights into the modularity function, it reveals structure that binary adjacency alone would miss: two nodes connected by a strong tie are treated as more similar than two nodes linked by a weak one. The Louvain algorithm is the dominant practical implementation.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.
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ScholarGateComparar métodos: Weighted Community Detection · Weighted Social Network Analysis. Recuperado em 2026-06-19 de https://scholargate.app/pt/compare