Gephi - Metriky
Avg Clustering Coefficient
The clustering coefficient, along with the mean shortest path, can indicate a "small-world" effect.The neighborhood of a node, u, is the set of nodes that are connected to u. If every node in the neighborhood of u is connected to every other node in the neighborhood of u, then the neighborhood of u is complete and will have a clustering coefficient of 1. If no nodes in the neighborhood of u are connected, then the clustering coefficient will be 0.
Avg Path Lenght
The average graph-distance between all pairs of nodes.Connected nodes have graph distance 1. The diameter is the longest graph distance between any two nodes in the network. (i.e. How far apart are the two most distant nodes).
Two measures derive from the distance: Betweenness Centrality and Closeness Centrality.
Centrality
http://en.wikipedia.org/wiki/Betweenness#Betweenness_centralityNode Betweenness Centrality measures how often a node appears on shortest paths between nodes in the network.
Betweenness Centrality
Node Betweenness Centrality measures how often a node appears on shortest paths between nodes in the network.Closeness Centrality
The average distance from a given node to all other nodes in the network.Connected Components
Determines the number of connected components in the network.Degree
The degree of a node is the number of edges that are adjacent to the node.Degree Power Law
It measures how closely the degree distribution of a network follows a power-law scale.Diameter
The maximal distance between all pairs of nodes.Eigenvector Centrality
A measure of node importance in a network based on a node's connections.Graph Density
Measures how close the network is to complete. A complete graph has all possible edges and density equal to 1.HITS
The HITS metric determines two values for a page: its authority, which estimates the value of the content of the page, and its hub value, which estimates the value of its links to other pages.Description
Actually computes two different scores: hubs and authority. The authority score indicates the value of the page (node) itself and hubs estimates the value of the links outgoing from the page (node). Hits is an iterative algorithm at each iteration:
Update the authority value of each node to be the sum of the hub values for every node it has a link into.
Update the hub values for each node to be the sum of the authority values that it has a link into.
Normalize the hub and authority scores for all nodes by normalizing each value by the system sum for each value.
Repeat these steps (assumingly until the values no longer
fluctuate).
Modularity
Measures how well a network decomposes into modular communities.A high modularity score indicates sophisticated internal structure.
This structure, often called a community structure, describes how the the network is compartmentalized into sub-networks. These sub-networks (or communities) have been shown to have significant real-world meaning.
Randomizing the algorithm can produce a better decomposition resulting in a higher modularity score, however randomizing will increase computation time.
PageRank
The Objective should define how the metric can be used, for which purpose etc.An iterative algorithm that measures the importance of each node within the network. The metric assigns each node a probability that is the probability of being at that page after many clicks. The page rank values are the values in the eigenvector that has the highest corresponding eigenvalue of a normalized adjacency matrix A'. The standard adjacency matrix is normalized so that the columns of the matrix sum to 1.
