Spectral Community Detection for Sparse Networks R package sparsecommunity version 0.1.1 Implements spectral clustering algorithms for community detection in sparse networks under the stochastic block model ('SBM') and degree-corrected stochastic block model ('DCSBM'), following the methods of Lei and Rinaldo (2015) <doi:10.1214/14-AOS1274>. Provides a regularized normalized Laplacian embedding, spherical k-median clustering for 'DCSBM', standard k-means for 'SBM', simulation utilities for both models, and a misclustering rate evaluation metric. Also includes the 'NCAA' college football network of Girvan and Newman (2002) <doi:10.1073/pnas.122653799> as a benchmark dataset, and the Bethe-Hessian community number estimator of Hwang (2023) <doi:10.1080/01621459.2023.2223793>. Software Depends: R (>= 4.0.0) Imports: graphics, Matrix, methods, RSpectra, stats Suggests: irlba, clue, igraph, igraphdata, testthat (>= 3.0.0), knitr, rmarkdown Neil Hwang <neil.hwang@bcc.cuny.edu> Comprehensive R Archive Network (CRAN) Neil Hwang [aut, cre] (ORCID: <https://orcid.org/0000-0002-5175-9397>) GPL-3 2026-04-08 application/tgz https://CRAN.R-project.org/package=sparsecommunity doi:10.32614/CRAN.package.sparsecommunity en-US