What is network analysis?

At its most basic, a network can be defined as a collection of ‘nodes’ (things like people, products, or web pages) connected by relationships or associations of some kind (known as ‘edges’).

A simple network, or 'graph', showing nodes and edges.

A simple network, or ‘graph’, showing nodes and edges.

The fundamental insight of network analysis is that a node’s position in the network reflects its importance.

For example, a website at the centre of a network of links, and a person at the centre of a community of people, will both have more importance or influence than others at the fringes.

Modelling a real-world phenomenon as a network therefore gives us at least one insight we otherwise wouldn’t have had.

Network analysis can reveal much more than this, however. For example, using network analysis we can:

  • identify communites, or other groups of similar nodes (eg similar websites)
  • understand how information, behaviours or even diseases flow through a network of contacts
  • track network change over time
  • overlay the network with other metrics and understand how measures such as network centrality correlate with, for example, wealth or opportunities for promotion within a company
  • visualise the network to get a bird’s eye view.

The insights of network analysis are surprisingly consistent across networks of various types – whether online or offline, and whether the nodes are people, websites, concepts or even words.

Once you start looking for networks and network effects, you see them everywhere.