## Degree Centrality

The degree of a node is the number of adjacent nodes. Thus a vertex with a high degree is connected to a lot of other vertices. In social networks we could find opinion leaders (persons with a lot of influence/friends) by using this centrality metric. Better degree centrality means higher probability of receiving information.

## Closeness Centrality

The farness of a node `n`

is defined as the sum of its distances from all other nodes, and its closeness is defined as the reciprocal of the farness (Bavelas).

## Betweenness Centrality

Betweenness centrality quantifies the number of times a node acts as a bridge along the shortest path between two other nodes. This metric is good for selecting nodes for epidemic spreading.

# TODO

- Examples
- Cluster Coeff.