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Clustering

In this video Wander Jager discusses that networks can display groups of people having close ties, which relates to the concept of “clustering”.
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SPEAKER 1: Another interesting property of networks is their clustering. You can imagine this as the number of people you meet in your immediate neighbourhood, versus the people you occasionally meet in different places. In network science, the clustering coefficient expresses the ratio of links between nodes that are close, versus links that are rewired to distant nodes. We just saw that the average path length very quickly reduces when you rewire some links, because most nodes remain connected with their local neighbours. Hence, some rewiring does not have major consequences on the clustering, and the clustering coefficient remains high. However, when we decide to rewire all links, all the nodes are randomly rewired to other nodes, resulting in a random network.
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As you can observe, in such a random network, the average path length is small, and the clustering coefficient is very low.

In the hunter gatherer society people were living in closely knit social groups. In network theory we speak of highly clustered groups.

When different clusters exist within a large network, and you rewire some of the links within clusters to improve the connections between these clusters, information may travel faster through the network.

Today we have many more possibilities to connect people in different clusters than in the hunter gatherer society. Just think of how the inventions of writing, printing, telephony, radio, television and the internet each had an enormous impact in how ideas and news could spread through society. Average path length is a word used in network theory to express how many links are needed to make a connection between two random nodes in a network.

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Social Network Analysis: The Networks Connecting People

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