Complex Networks
Complex networks refer to networks that exhibit non-trivial topological features, such as high clustering, small-worldness, and scale-free degree distributions. In data science, complex networks are used to model and analyze various types of systems, such as social networks, biological networks, transportation networks, and telecommunication networks. The analysis of complex networks involves the study of network properties, such as degree distribution, centrality measures, community structure, and network resilience. Complex network analysis techniques include network visualization, network clustering, network motif analysis, and network modeling. The study of complex networks has applications in various fields, such as epidemiology, finance, physics, and computer science.
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