Network Analysis

At its most basic level, a network is any connection to anything else. In order for a network to be meaningful, it has to be a system of elements or entities that are connected by relationships. These relationships are the defining feature of networks, as opposed to content or components. People study networks because they believe that the network itself is in some way significant and that the parts that make up the network are interdependent, not independent. Network analysis can be used to identify emerging patterns within a dataset. One kind of network analysis is social network analysis, which analyzes social structures through the use of networks. The following resources provide an excellent starting point for understanding what network analysis is:

• Social Network Analysis
• What is Social Network Analysis? by Prof Martin Everett (video)
• A Quick Look at Social Network Analysis (video)

Glossary of terms

• Node: Represents an entity (e.g., person)
• Edge: Represents a relationship between two nodes. Can have different weights to represent the strength of the relationship
• Path/Connector: Indirect relationships between nodes through another node
• Cluster: A group of nodes that has interrelationships
• Degree: Number of connections (edges) for a node. Nodes with more degrees have more direct relationships
• Closeness: How close or far a node is to all other nodes. Nodes with better closeness have more indirect relationships
• Betweenness: How often a node is on the shortest path. Nodes with more betweenness connect clusters
• Centrality: A measure of how many other nodes are related

Network analysis projects

• Kindred Britain
• Republic of Letters
• The Viral Texts Project