Exploring Social Network Structures Through Friendship-Driven Community Detection with Association Rules Mining R package arlclustering version 1.0.5 Implements an innovative approach to community detection in social networks using Association Rules Learning. The package provides tools for processing graph and rules objects, generating association rules, and detecting communities based on node interactions. Designed to facilitate advanced research in Social Network Analysis, this package leverages association rules learning for enhanced community detection. This approach is described in El-Moussaoui et al. (2021) <doi:10.1007/978-3-030-66840-2_3>. Software Imports: methods, igraph, arules, grDevices, graphics, stats Suggests: testthat (>= 3.0.0), knitr, rmarkdown, tidyr Mohamed El-Moussaoui <med.elmoussaoui.ced@gmail.com> Comprehensive R Archive Network (CRAN) Mohamed El-Moussaoui [aut, cre], Mohamed Hanine [aut], Ali Kartit [ths], Tarik Agouti [rev] GPL-3 2024-09-11 application/tgz https://CRAN.R-project.org/package=arlclustering doi:10.32614/CRAN.package.arlclustering