Community Detection

Community detection is the process of identifying groups of nodes (or communities) within a network that are more densely connected to each other than to the rest of the network. In data science, community detection is used to analyze complex networks such as social networks, biological networks, and transportation networks. The goal is to identify groups of nodes that share similar properties or functions, and to understand the relationships between these groups. Community detection algorithms can be divided into two categories: hierarchical and non-hierarchical. Hierarchical algorithms group nodes into nested clusters, while non-hierarchical algorithms group nodes into non-overlapping clusters. Some popular community detection algorithms include Louvain method, Girvan-Newman algorithm, and Infomap algorithm.
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