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In mathematics and computer science, connectivity is one of the basic concepts of graph theory: it asks for the minimum number of elements (nodes or edges) that need to be removed to separate the remaining nodes into two or more isolated subgraphs. It is closely related to the theory of network flow problems.

The degree of a node is the number of connections that it has to other nodes in the network. In a social network if you have 100 friends then the node that represents you has a degree of 100. Path length is simply the distance between two nodes, measured as the number of edges between them.

By counting how many nodes have each degree, we form the degree distribution Pdeg(k), defined by Pdeg(k)=fraction of nodes in the graph with degree k. For this undirected network, the degrees are k1=1, k2=3, k3=1, k4=1, k5=2, k6=5, k7=3, k8=3, k9=2, and k10=1.

By counting how many nodes have each degree, we form the degree distribution Pdeg(k), defined by Pdeg(k)=fraction of nodes in the graph with degree k. For this undirected network, the degrees are k1=1, k2=3, k3=1, k4=1, k5=2, k6=5, k7=3, k8=3, k9=2, and k10=1.

For a vertex, the number of head ends adjacent to a vertex is called the indegree of the vertex and the number of tail ends adjacent to a vertex is its outdegree (called branching factor in trees).

In the study of graphs and networks, the degree of a node in a network is the number of connections it has to other nodes and the degree distribution is the probability distribution of these degrees over the whole network.

The degree of a node in an undirected graph is the number of edges incident on it; for directed graphs the indegree of a node is the number of edges leading into that node and its outdegree, the number of edges leading away from it (see also Figures 6.1 and 6.2).