Bayesian degree-corrected stochastic blockmodels for community detection

DOI10.1214/16-EJS1163zbMath1395.62370arXiv1309.4796OpenAlexW2963683224MaRDI QIDQ315413

Lijun Peng, Luís Carvalho

Publication date: 21 September 2016

Published in: Electronic Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1309.4796

zbMATH Keywords

community detectioncanonical remappingcentroid estimationcommunity detection in networkslabel non-identifiability

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Social networks; opinion dynamics (91D30) Applications of statistics to social sciences (62P25) Bayesian inference (62F15)

Related Items (5)

Bayesian degree-corrected stochastic blockmodels for community detection ⋮ Variational Bayesian inference for bipartite mixed-membership stochastic block model with applications to collaborative filtering ⋮ Dynamic degree-corrected blockmodels for social networks: A nonparametric approach ⋮ Weighted stochastic block model ⋮ Modeling the social media relationships of Irish politicians using a generalized latent space stochastic blockmodel

Uses Software

• BayesLogit
• BayesDA

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