This document discusses social network analysis and its key concepts. It defines different types of networks like ego-centric and socio-centric networks. It also discusses network concepts such as density, cliques, brokers, and peripherals. The document outlines advantages of social network analysis in identifying important actors and understanding communication patterns. It also notes limitations like relying on snapshots and survey responses. Finally, it provides an example of how social network analysis was used to study business connectivity in Bristol.

1. Social Network
Analysis
‘...a central Jack or a periphery Bob?’
-Alcott & Christopoulos

2. Network Type
Example: Ego-Centric
• Ties in these networks are
defined by a single central
actor/node (including perceived
ties between other actors).
• Ego-centric networks ...provide
network analysts and researchers
with interesting and useful data
about the roles individuals
adopt… -Fisher
Alternatives:
• Socio-centric
• One Mode
• Two Mode

3. Network Density
Example: Sparse
• Ego-centric networks are
vulnerable if the central node
is removed and you are unable
to recruit any other actor who
is structurally equivalent.
Alternatives:
• Dense – networks where the
majority of nodes are directly
linked to each other are more
resilient as there is little/no
disruption to communication
flows if an actor is removed.

4. Cliques
Example: 16, 7, 8
• A clique is a subgroup of
actors who are all directly
connected to one another
and no additional network
member exists who is also
connected to all members of
the subgroup.
-Hawe, Webster & Shiell

5. Brokers
Good or bad?
• Described as …individuals
who are the glue that holds
a social network together …
• In most cases, knowledge
brokers are good, but there
are times when they are
hoarders of information or
power brokers.
-Tennant

6. Peripherals
Not necessarily out-on-a-limb...
Remember:
...some organisations within an
inter-organisational network can
exercise power by refusing to lend
their credibility to the network.
They remain on the periphery
structurally, but are able to
influence the direction the
network takes entirely because of
their size, reputation, or through
the power of sanctions.
-Hawe, Webster & Shiell

7. Advantages of SNA
• Key actors identified by the
network are often missed by
hierarchical/organisational
related approaches.
• Visual impact: From a good
visualization, the observer can
begin to understand
communication
patterns, including who on the
nursing unit may influence the
flow of information (e.g., act as a
gatekeeper) or who has more or
authority due to their
coordination role in the network.
-Effken & Benham-Hutchins

8. Limitations of SNA
• Identifying isolates in the
workplace/school setting
etc must be approached
with caution
• Findings tend to
represent ‘snapshots’;
follow-up investigation
often recommended to
spot trends over time
• Often survey-based;
vulnerable to low
response rate and
inaccuracies
Image credit: spaceodissey via flickr

9. SNA in action:
business connectivity in Bristol
• ‘Engaging with this project, individual actors have been able to
discern weaknesses in their network position and detect
opportunities in those that reciprocate a collaboration interest.
• At the same time they have been able to gain an overview of the
structure of interactions among others and potentially determine
an optimal strategy for their own network interactions.
• By improving on their cognitive map of the network they are
effectively improving their horizon and making an informed
decision on whether it is best for them to meet a central Jack or a
peripheral Bob. ‘
-Alcott & Christopoulos

10. Bibliography
• ALCOTT, T. and CHRISTOPOULOS, D.C . (2011). Is it important to know Jack? Using
social network analysis to assess regional business connectivity in Bristol. [online].
Procedia - Social and Behavioral Sciences, 10, 90-97. Last accessed 15 July 2012 at:
http://www.sciencedirect.com/science/article/pii/S1877042811000139
• EFFKEN , J. and BENHAM-HUTCHINS, M. (2011). Technology-Enhanced Social
Network Analysis: An Old Idea Whose Time Has Come—Again. (Issues, Impacts
and Insights Column). [online]. Online Journal of Nursing Informatics (OJNI),15 (1).
Last accessed 15 July 2012 at: http://ojni.org/issues/?p=326
• FISHER, D. (2005). Egocentric Networks To Understand Communication. [online].
IEEE Internet Computing. 9(5). Last accessed 15 July 2012 at:
http://research.microsoft.com/pubs/69319/ieee_egocentric.pdf
• HAWE, P., WEBSTER, C. and SHIELL, A. (2004). A glossary of terms for navigating
the field of social network analysis. [online] Journal of Epidemiol Community
Health. 58:971-975. Last accessed 15 July 2012 at:
http://jech.bmj.com/content/58/12/971.full
• TENNANT, N. (2012). Social Networks for Talent Identification: Is the 9-Box Dead?
[online]. Management Innovation eXchange. 24/04/12. Last accessed 15 July
2012 at: http://www.managementexchange.com/story/social-networks-talent-
identification-9-box-dead