Network mapping

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by Drew Mackie

Scottish Borders towns network diagram

It has become fashionable to talk of networks of organisations, people, computers, transport and so on. In organisations there is talk of being more “networky” and getting away from the older more hierarchical ways of doing things. Conferences are organised around “networking” both formal and informal.

Yet, the more that you listen to this network talk the more you realise that people mean very different things by the term “network”. The purpose of this paper is to explore what network thinking means and how networks can be mapped and analysed.

Why is this important and useful? The structure of a network will affect how influence and information is distributed. Certain members will be potentially more influential because of their position in the network. Mapping the network can give guidance on the easiest ways to distribute information, the links that
should be there to improve the network and how to avoid bottlenecking. It is used by commercial and
government organisations to plot situations as diverse as:

  • structures of trust, advice and communication within an organisation or group of organisation
  • planning the development of network
  • improving the functioning of project teams
  • mapping communities of interest or expertise
  • identify centres of expertise
  • indicate key organisations and links to encourage community cohesion

What is a network?

The first thing to be said is that a network is not just a list. The term implies a set of connections between its members. These connections may consist of the flows of information , power, money or whatever but the implication is that an influence of some sort is passing from one to the other.

Networks can be dense or sparse – meaning that the number of connections is great or small. The total number of connections possible in any group of members where n is the number of members in the group is given by the formula:

Thus, a network of 10 members has a total of 45 possible connections. The density of a network is measured by comparing the number of actual links with the number of possible links and expressing this as a percentage. For all members of a network to be connected to it the number of links must be at least n-1. A well connected organisation will have a density of around 15% to 20%. Research shows that the best connected organisations allow its members to connect within two steps – ie that influence drops off sharply if it has to exert itself through more than two connectors. The exception to this is a strongly hierarchical organisation with well defined chains of command.

The following examples show the “kite” diagram developed by David Krackhardt of Carnegie Mellon University and used to illustrate the properties of a network. Ten people make up the network and they are related in different ways shown by the linking lines. The shading indicates how various members
perform according to a number of different measures.

Fig 1 – Numbers of Connections (Degree centrality)

Fig 1 - Numbers of Connections (Degree centrality)

This shows an assessment of how many connections members have. This is known as “Degree centrality”.
Diane has more connections to other members. Garth and Fernando are also well connected. Jane is the worst connected person in the network with only 1 connection.


Influence over a network is not just a matter of how many connections you have. You may be connected to many people who have few connections to anybody else. Although degree centrality is easy to calculate it doesn’t tell the whole story.

Fig 2 – Shortest Pathways (Closeness centrality)

Fig 2 - Shortest Pathways (Closeness centrality)

This shows how close various members are to all the others. This is measure of how central a person is to the workings of the network. Both Fernando and Garth are within 3 connections of all other people in the net. Diane is still central but is 4 connectors away from Jane.

This measure is important because research in organisations shows that influence fades if you need more than 2 links to get to another member.

It also indicates which members will have general influence over the network because of their position. If you want information spread fast, feed it to the most central members.

Fig 3 – Gatekeepers (betweenness centrality)

Fig 3 - Gatekeepers (betweenness centrality)

This shows a different sort of centrality. There are people who are the sole or main connectors to parts of the network. Links from the rest of the network to Ike or Jane all have to pass through Heather. She is a gatekeeper to a subsection of the network. This is known as “betweenness” centrality. People or
organisations in this position can have great influence on the flow of information.

This is good in that they ensure that the network is fully connected – but potentially harmful in that they can filter that information according to their own agenda or make the network vulnerable to their departure.

Practical uses

So how can we use network mapping and analysis to help our regeneration activities? We have been involved in a number of projects that have used such mapping.

  • a study of community cohesion in Pendle, Lancashire
  • organising a conference on links between organisations involved in environmental projects in North Lanarkshire
  • working with Government Departments in England to encourage mutual learning in methods of Public Involvement
  • comparing the organisational structure of the Crown Street project in Glasgow’s Gorbals at various stages of its development

The same procedure was used in each:

  • interview or survey organisations with a common interest and get them to specify their working links to each other. This is either done by getting them to list these links or to draw them on a constantly developing map
  • draw the simplest possible map of these relationships
  • analyse the various forms of centrality and identify potential links that could improve patterns of Advice, Trust or Communication within the network and advise on key organisations that are central to the operation of the network

More examples
Fig 4 – Government Departments and Public Involvement

Government Departments and Public Involvement

As part of a learning programme for Departments involved in Public Engagement, we asked participants to list the three organisations that they worked with most. These had to be operational links – sitting on the same committee didn’t count. This map is now being extended to show a wider range of organisations and to provide a “road map” for those concerned with public involvement. Shading shows organisations with the greatest betweenness centrality.

Fig 5 – Map of Organisations involved in Environmental Projects in North Lanarkshire

Map of Organisations involved in Environmental Projects in North Lanarkshire

The map below was developed for a conference on development of a network based on environmental projects. This version was developed before the conference through a short questionnaire. A session in the conference further developed the map and this was used as a the basis for analysis that showed the existing and potential centrality of the local authority in developing the network – but also the shortcomings of links within the authority itself (yellow nodes).

Fig 6 – Map of Organisations involved in Community Cohesion in Pendle

Map of Organisations involved in Community Cohesion in Pendle

This map was prepared using a series of interviews and leaving a basic map for completion by the interviewees. The subsequent analysis revealed a series of local “broker” organisations that acted as intermediaries between regional organisations and local projects. These are shown against a blue background and are totally connected – ie all brokers link with all other brokers. The network is particularly well connected compared to some other community cohesion networks in Lancashire.


  1. As can be seen from the above examples, mapping can be a practical tool in defining a network and making some assessment of its likely performance. It is a well recognised technique that can uncover some unexpected issues and opportunities.
  2. Simple networks can be analysed visually. Networks of any size will need computer support in drawing the simplest diagram and in analysing the various forms of centrality.
  3. Maps can be used as “clickable” way finders on the internet. Each node can contain a web address that leads to an organisation’s website.

This post was contributed by Drew Mackie of Drew Mackie Associates

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