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Network science, also known as network theory or graph theory, is an interdisciplinary field that studies the structure, behavior, and dynamics of complex networks. A network is a collection of nodes (also called vertices) connected by edges (also called links or ties). These nodes can represent various entities, such as individuals, computers, cities, proteins, or any other discrete objects, while the edges represent the relationships or interactions between these entities.

The study of networks has applications in a wide range of fields, including computer science, sociology, biology, physics, economics, transportation, and many others. Some common types of networks include social networks (e.g., Facebook, Twitter), communication networks (e.g., the internet), biological networks (e.g., neural networks, gene regulatory networks), and transportation networks (e.g., road networks, airline networks).

  1. Network Measures: Metrics that describe various properties of a network, such as node degree (the number of connections a node has), clustering coefficient (the tendency for nodes to form clusters), centrality (the importance of a node within a network), and (the tendency of nodes to connect to similar nodes).


  3. Small World Phenomenon: The observation that most real-world networks exhibit short average path lengths between nodes, meaning that any two nodes can be connected by a relatively small number of steps. This property is often referred to as "six degrees of separation."

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