Complex network analysis

Publié le: 12 septembre 2022
sur la chaîne: Computational Linguistics

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Complex network analysis refers to the study of large networks that possess properties which could not be found otherwise in simple graphs. They generally represent bigger systems, like the networks of all web pages on the WWW. It has emerged as a new field comprising basics of graph theory, community detection and machine learning. These networks can be studied in static or dynamic arrangement, depending on the nature of the problem and the data available. Complex networks are of two basic types that are scale-free networks and random or small-world network. Scale-free networks are more loosely connected, having long tails and fewer paths between pairs of nodes. On the other hand, random networks are more balanced in connection, where every node can be reached from every other node in fewer hops. #complexnetworkanalysis #socialnetworkanalysis #scalefreenetworks

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