Graph clustering is a technique used to group nodes in a graph into clusters or communities based on their connections. Each cluster contains nodes that are more closely related to each other than to those in other clusters. This method is useful in various fields, such as social network analysis, where it helps identify groups of friends or communities within a larger network. The process typically involves algorithms that analyze the structure of the graph, such as K-means or Louvain method. By identifying these clusters, researchers can gain insights into the underlying patterns and relationships within the data, making it easier to understand complex systems.