Centrality

Centrality is a measure of the importance of a node or an entity within a network. In data science, centrality is used to identify the most influential nodes in a network, which can help in understanding the structure and dynamics of the network. There are different types of centrality measures, such as degree centrality, betweenness centrality, and eigenvector centrality. Degree centrality is based on the number of connections a node has, while betweenness centrality is based on the number of shortest paths that pass through a node. Eigenvector centrality takes into account the centrality of a node's neighbors, giving more weight to nodes that are connected to other highly central nodes. Centrality measures can be used in various applications, such as identifying key players in social networks, detecting anomalies in communication networks, and predicting the spread of diseases in epidemiological networks.
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