Description
Graph clustering helps researchers and data analysts find natural groups in networks by simulating flow between connected nodes. It is useful for biological networks, social graphs, document links, and other datasets where communities are more important than individual edges.
This is a specialized algorithmic tool, usually used from scripts or terminal workflows. Results depend on input graph quality and chosen parameters, so clusters should be interpreted as analytical evidence rather than automatic truth.