Comparar métodos

	Detección de Comunidades	Análisis de Redes del Ego	Análisis de Redes Sociales
Campo	Análisis de redes	Análisis de redes	Análisis de redes
Familia	Process / pipeline	Process / pipeline	Machine learning
Año de origen	2002–2019 (algorithm family)	1992 (Burt); foundational measurement formalised by Marsden 2002	1934 (sociometry); 1994 (modern formalization)
Autor original	Louvain: Blondel et al. (2008); Leiden: Traag et al. (2019); Girvan-Newman: Girvan & Newman (2002); Infomap: Rosvall & Bergstrom (2008)	Ronald S. Burt (structural holes framework); Peter V. Marsden (egocentric measures)	Moreno, J.L.; formalized by Wasserman & Faust
Tipo	Graph-partitioning / clustering algorithm family	Descriptive / relational network analysis	Structural/relational analysis framework
Fuente seminal	Blondel, V.D., Guillaume, J.-L., Lambiotte, R. & Lefebvre, E. (2008). Fast Unfolding of Communities in Large Networks. Journal of Statistical Mechanics, 2008(10), P10008.	Burt, R.S. (1992). Structural Holes: The Social Structure of Competition. Harvard University Press. ISBN: 9780674843714	Wasserman, S. & Faust, K. (1994). Social Network Analysis: Methods and Applications. Cambridge University Press. ISBN: 978-0-521-38707-1
Alias	graph clustering, network partitioning, Topluluk Tespiti (Louvain, Girvan-Newman, Leiden)	personal network analysis, egocentric network analysis, Ego Ağı Analizi (Personal Network Analysis)	SNA, network analysis, sociometric analysis, relational analysis
Relacionados	5	6	5
Resumen	Community detection is a family of graph-partitioning algorithms that discover densely connected sub-groups — communities — within a network. First formalised through the modularity measure by Girvan and Newman (2002), the field advanced rapidly with the Louvain method (Blondel et al., 2008), the Leiden refinement (Traag et al., 2019), and the information-theoretic Infomap approach. All variants answer the same question: which nodes cluster together more tightly among themselves than with the rest of the network?	Ego network analysis examines the personal network of a focal individual — the ego — by mapping their direct contacts (alters) and the ties those contacts share with one another. Formalised through Ronald Burt's structural holes framework (1992) and Marsden's egocentric measurement approach (2002), the method produces ego-level indicators such as network size, density, constraint, and brokerage role that reveal how each individual's social position shapes their access to information, resources, and influence.	Social Network Analysis (SNA) is a structural method that maps and measures relationships and flows between people, groups, organizations, or other entities modeled as nodes connected by ties (edges). Rather than focusing on individual attributes, SNA reveals how the pattern of connections shapes behavior, influence, information flow, and outcomes within a system.