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Latent Space Network Model×Blockmodeling×
BidangSociologySociology
KeluargaMachine learningProcess / pipeline
Tahun asal20021976
PencetusPeter Hoff, Adrian Raftery & Mark HandcockHarrison White, Scott Boorman & Ronald Breiger
TipeLatent-variable model placing actors in an unobserved social spaceNetwork partitioning into positions and a reduced role structure
Sumber perintisHoff, P. D., Raftery, A. E., & Handcock, M. S. (2002). Latent space approaches to social network analysis. Journal of the American Statistical Association, 97(460), 1090–1098. DOI ↗White, H. C., Boorman, S. A., & Breiger, R. L. (1976). Social structure from multiple networks. I. Blockmodels of roles and positions. American Journal of Sociology, 81(4), 730–780. DOI ↗
Aliaslatent space model, latent position model, LSM, latent distance modelblock modeling, blockmodel analysis, generalized blockmodeling, CONCOR
Terkait44
RingkasanThe latent space network model represents each actor as a point in an unobserved low-dimensional 'social space' and makes the probability of a tie between two actors a decreasing function of the distance between their points. Introduced by Peter Hoff, Adrian Raftery, and Mark Handcock in 2002, it gives social networks a geometric interpretation in which proximity captures unobserved similarity, and it automatically reproduces transitivity and homophily through the geometry.Blockmodeling is a family of methods that simplify a social network by partitioning its actors into positions — groups of actors who are equivalent in their pattern of ties — and summarizing the relations between positions as a compact image, or reduced role structure. Introduced by Harrison White, Scott Boorman, and Ronald Breiger in 1976, it shifts attention from individuals to the structural roles they occupy.
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ScholarGateBandingkan metode: Latent Space Network Model · Blockmodeling. Diakses 2026-06-24 dari https://scholargate.app/id/compare