awesome-community-detection

Why we included this project

Community detection is the part of graph analytics that finds clusters and communities in networks, and this collection maps the research literature on it. Each paper is listed alongside a working implementation, so you can read a method and then run it without digging for code. The entries are grouped by technique, from matrix factorization and deep learning to label propagation, spectral methods, and temporal approaches, which helps when you are comparing families of algorithms for a particular dataset. It is a curated index rather than a piece of software, so its real value is the breadth of methods and the links to reproducible code. Researchers surveying the field will find it useful, and so will practitioners who want a starting point before testing a few candidates on their own graphs.