Cogito’s graph analytics provide tools to determine patterns of interaction between actors and groups in social networks and answer questions such as:

• What subgroups exist in the network?
• How do these subgroups interact with each other?
• What is the overall structure of the network?
• What are the roles (central/peripheral) of network members?

OPTIMAL PATH FINDING

Prior to version 2.4, the Graph Engine treated the problem of finding optimal paths only in terms of the number of connections in the paths between a pair of given nodes. In the Graph Engine API, this capability is called a "Shortest Path" search. Version 2.4 of the Graph Engine adds a "Weighted Path" search, which can find the paths between a pair of given nodes where the sum of the weight of the individual arcs in the path is greatest or smallest (depending on whether you define high or low as optimal). So now you can analyze graphs in terms of the number of connections or the value of the connections.

CENTRALITY METRICS

Cogito's graph analytics includes the following key measures of network centrality:

Degree	A count of the number of arcs terminating at each node.
Closeness	The ratio of the number of nodes in the graph over the sum of the shortest paths between the given node and all other connected nodes.
Betweenness	The ratio, for each node, of the number paths between two other nodes that pass through the node over the number of paths between the two other nodes.
Bridging	The product of the betweenness centrality and the bridging coefficient of the node.

The table below shows the how efficient a graph database is when compared to a relational database for basic Centrality calculations.

Key Benefits:

• Evaluate social networks for groups and roles
• See how individuals and groups are interrelated
• Quantify centrality factors
• Determine key players, spanners and central figures