Network Clustering & Connectedness HD

For the full course see: https://goo.gl/iehZHU Follow along with the course eBook: https://goo.gl/i8sfGP The way in which a network is connected plays a large part in how we will analyze and interpret it. When analyzing connectedness and clustering we are asking how integrated or fractured the overall network system is, how these different major sub-systems are distributed out and their local characteristics. Produced by: http://complexitylabs.io Twitter: https://goo.gl/ZXCzK7 Facebook: https://goo.gl/P7EadV LinkedIn: https://goo.gl/3v1vwF Transcription excerpt: The way in which a network is connected plays a large part in how we will analyze and interpret it. When analyzing connectedness and clustering we are asking how integrated or fractured the overall network system is, how these different major sub-systems are distributed out and their local characteristics. A graph can said to be connected if for any node in the graph there is a path to any other node, when the graph is not connected then there will be a number of what we call components to it. A component is a sub-set of nodes and edges within a graph that are fully connected, thus for a node to be part of a component it must be connected to all the other nodes in that component. A cluster is simply a subset of the nodes and edges in a graph that possess certain common characteristics, or relate to each other in a particular ways forming some domain-specific structure. So where as a component is simply referring to whether a given set of nodes are all connected or not, a cluster is referring to how they are connected and how much they are connected that is the frequency of links between a given subset of nodes. In order to model the degree of clustering of a subset of nodes we simply take a node and look at how connect a node it links to is to other nodes that it is also connected to. So if this was a social network of friends we would be asking how many of your friends know your other friends, the more your friends are interconnect the more clustered the subset is said to be. This clustering within social networks is also called a clique, a clique is a group of people who interact with each other more regularly and intensely than others in the same setting. Within this social context clustering can be correlated to homophily, where homophily describes the phenomenon where people tend to form connections with those similar to themselves, as captured in the famous saying “birds of a feather flock together”. We might think of clustering coming from the fact that the interaction between nodes with similar attributes will often require less resources than interaction between nodes with different attributes, for example between to cultures there may be a language barrier or between different devices on a network that might have different protocols, or clustering may be due to physical constraints of the resource expenditure required to maintain them over a greater distance, thus resulting i