Geoff in 2008
Geoff's Self Portrait
Geoff's Bladerunner Portrait

Part of my research involves attempting to understand the complexity of networks. In order to do this I am analysing Ego-centred or Personal Social Networks (PSNs).

 

Data for this mapping exercise was collected in a series of focus groups where nodes were asked to identify other nodes with which they had contact on a daily, weekly, monthly or annual basis. Data was then inserted into a matrix where connections were given a binary value, i.e., 1 for a connection between two nodes; O for no connection between nodes.

 

Problems clearly exist in using such a methodology to estimate network parameters:-

 

1. Most people appear to be relatively poor at estimating their number of contacts reliably.
2. Methodologies to overcome this difficulty (such as keeping records of contacts over a period of time) can be both time-consuming and labour intensive.
3. The number of contacts changes over time.
4. The number is highly sensitive to personal definitions of meaningful contacts.

 

Despite the above, the exercise does serve to illustrate some of the complexities of PSNs.

 

The data was analysed using a freeware tool developed by Marius I. Benta called AGNA (Applied Graph & Network Analysis).

 

To the left is the PSN of the Strategic Co-ordinator of Sunderland Community Development Network. The node at the centre of the network is the co-ordinator. The next four nodes from the co-ordinator are the network's development workers.

 

There are 33 nodes in the network displaying 348 connections. The total number of connections possible in any given network is n*n-1/2, i.e., in a network of 33 nodes: 33*32/2 = 528. So, in a relatively small network of 33, there are 180 (34%) unmade connections.

 

The most highly connected nodes in the network are those with professional organisations responsible for the strategic development of the network.

 

Insight¦Download¦Networks¦Links¦Quotes¦Curriculum Vitae

  Intro to KM¦Contact