1. Social Networks
Corina Ciubuc

2. Index Introduction Social Network Analysis (SNA) Metrics in SNA
Example

3. Social Networks

4. What is a Social Network ?
Network – a set of nodes, points or locations connected
Social Network -  a social structure made up of individuals (or organizations) called "nodes", which are tied (connected) by one or more specific types of interdependency, such as friendship, common interest
Social Network Analysis (SNA) - views social relationships in terms of network theory consisting of nodes and ties (also called edges, links or connections).

5. Social Network Analysis
Nodes - individual actors
within the networks
Ties - relationships between
the actors
The resulting graph-based
structures are often very
complex
To understand networks and
their participants, we evaluate
the location of actors in the network.

6. Measures in SNA
Degree - The count of the number of ties to other actors in the network. CD(v) = deg(v)
Betweenness - The extent to which a node lies between other nodes in the network. The measure reflects the number of people who a person is connecting indirectly through their direct links.

7. Measures in SNA (2)
Closeness - The degree an individual is near all other individuals in a network (directly or indirectly). Closeness is the inverse of the sum of the shortest distances between each individual and every other person in the network. 

8. Measures in SNA (3)
Bridge - An edge is said to be a bridge if deleting it would cause its endpoints to lie in different components of a graph. Tarjan Algorithm
Centralization - The difference between the number of links for each node divided by maximum possible sum of differences.

9. Measures in SNA (4)
Eigenvector centrality - A measure of the importance of a node in a network. It assigns relative scores to all nodes in the network based on the principle that connections to nodes having a high score contribute more to the score of the node in question.
Local bridge - An edge is a local bridge if its endpoints share no common neighbors. Unlike a bridge, a local bridge is contained in a cycle.
Path length - The distances between pairs of nodes in the network.

10. Example: Kite Network

11. Example (2)
Degree Centrality - Diane has the most direct connections in the network - the most active node in the network = a 'connector' or 'hub' in the network.
“The more connections, the better."
…… This is not always true
Betweenness Centrality - Heather has few direct connections …. but she has one of the best locations in the network = a 'broker' in the network.
“ Location, Location, Location."

12. Example (3)
Closeness Centrality - Fernando and Garth The pattern of their direct and indirect ties allow them to access all the nodes in the network more quickly than anyone else = they have the best visibility into what is happening in the network.
Boundary Spanners - Nodes that connect their group to others usually end up with high network metrics.
Network Centralization - A very centralized network is dominated by one or a few very central nodes.

13. References
“Social Network” – Retrieved from -
“Social Network Analysis, A Brief Introduction” Retrieved from -
Mislov A., Marcon M., Gummadi K., Druschel P., Bhattacharjee B - “Measurement and Analysis of Online Social Networks” - Retrieved from -

14. Questions