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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.
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