Using social network analysis in community development practice and research: a case study Gretchen Ennis * and Deborah West Abstract In 2010, we pr op osed that integ ratin g social ne twork anal ys is into community development practice may be a useful way to make overt the links betw een micro- and macro-level issues in communities, and for researching the impacts of community development work [Ennis, G. and West, D. (20 10) Exploring the pote ntia l of social netw ork analysis in asset-based community development pract ice and resear ch, Australian Social Work, 63 (4), 404–417]. This article presents research drawn from a community case study and provides a real example of how networkana ly sis can be embedded in commun ity dev elo pme nt pr ocesses. The research demons tra tes tha t social netw ork ana lyt ic tech niques can be useful in a range of ways, including: facilitating a critical analysis of ‘the communit y’ ; focusi ng communit y work pr oces se s; and pr oviding particular unders ta ndin gs abou t th e outcomes and impacts of community work. In summary , the findings demons tra te that social network analysis is a useful tool for facilitating community development and measuring the efficacy of community development projects. Introduction In the first instance, we wish to make clear that by ‘social network analysis’ we are discussing a research methodology and not the analysis of online social networks (such as Facebook or Myspace, etc). Social network analysis provides particular understandings about how people or other entities are * Address for correspondence: Gretchen Ennis, School of Health, Faculty of Engineering, Health, Science and the Environment, Charles Darwin University, Northern Territory 0909, Australia; email: gretchen. [email protected]& Oxford University Press and Community Development Journal . 2012 All rights reserved . For permiss ions, please email: journals.pe rmissio ns@o up.c om doi:10.1093/cdj/bss013 Advance Access publication 10 May 2012 40 Community Development Journal Vol 48 No 1 January 2013 pp. 40–57 atTheA u sraliaN atio n alU n iv ersity o n M ay 26, 2013http ://cdj. o x fo rdjo u rn als. o rg /D o w lo adedfro
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Locating components is a particularly useful process in exploratory
network analysis, where the researcher might be interested in finding out
whether structural sub-groups correlate with other attributes or variables,
such as gender or age.
In the pre-project participant diagram, there are three distinct networks
which are quite clear to see (Figure 1). These three networks are not
joined to one another by any connection. The component comprised of
actors [75, 69, 15, 17] is not connected to the main network in the
diagram. They form their own small network. Actors [44, 23, 27, 38]
form another small component, separate from the main sections of the
diagram. In terms of cultural group, the component [75, 69, 15, 17] identifies
as Aboriginal. Each of these actors also lives within Bagot Community, and
three of the four were active participants in the LNC project. While there isanother actor in the network who identifies as Aboriginal (v34), this actor
does not live in Bagot Community.
The component [44, 23, 27, 38] identifies as Australian and not belonging
to any other cultural group. When examining their data for other similar-
ities, it is revealed that they are direct neighbours, with houses adjoining
Figure 1 Structure diagram of the pre-project research participants. Cultural groups: black
identifies as ‘Aboriginal’ (5 people, 10.2 percent of network); white, being ‘born overseas’
(7 people, 14.3 percent of network); grey, ‘Australian’ and no other cultural group (37 people,
75.5 percent of network). Tie strength: thin line, weak tie; thick line, strong tie.
46 Gretchen Ennis and Deborah West
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one another (we will call them X-street residents). Other variables such as
age, gender, profession and family status did not reveal commonalities
between all four from that small network.
It is possible, therefore, to say that these two small components are
based on geography, or small geographic sub-communities, and perhaps
on cultural group (as both components contain only one cultural group
each). There is a Bagot Community component and an ‘X-street’ com-
ponent. The main component of the diagram, containing all other actors,
does not appear to have any significant similarities among actors, although
it is predominantly filled by the group ‘Australian and no other cultural
group’.
It is useful to consider the ‘average degree’ of the pre-project participant
diagram. An actor’s ‘degree’ ‘is the number of lines that are incident withit’, and equivalently ‘it is the number of actors adjacent to it’ (Wasserman
and Faust, 1994, p. 100). That is, the degree of an actor is the number of
ties coming to or from it. In a network of forty-nine actors, an actor with
a degree of 0 is connected to no one. An actor with a degree of forty-eight
is connected to every other actor in the network (other than themselves).
The average degree of a network is a good indicator of the cohesiveness
of the network. Table 1 provides an overview of the frequency distribution
of the degree of the actor in the pre-LNC project participant network.
Table 1 demonstrates that, on average, each participant in the pre-project
network is connected to 2.37 other actors in the network. Both the network
diagram and the frequency distribution demonstrate that the ‘most
connected’ actor is ‘v1’ with eleven connections to others, and there are
nineteen actors with connections to only one other.
Table 1 Distribution of the degree of pre-project research participants
Degree Frequency Frequency percentage
CumFreq CumFreq Representative
1 19 38.7755 19 38.7755 v2
2 13 26.5306 32 65.3061 v5
3 9 18.3673 41 83.6735 v6
4 4 8.1633 45 91.8367 v4
5 1 2.0408 46 93.8776 v21
6 2 4.0816 48 97.9592 v7
11 1 2.0408 49 100.0000 v1
Sum 49 100.0000
Sum 116.0000000Arithmetic mean 2.36735
Median 2.0000000
Standard deviation 1.80356
Actors: 49; ties: 61; density: 0.0493197; the lowest value: 1; the highest value: 11.
Social network analysis in community development practice and research 47
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practice and research so that workers and community members could
better understand the impacts of their efforts.
Funding
The research was carried out as part of a PhD program undertaken by
Gretchen Ennis at Charles Darwin University. Gretchen received an Aus-
tralian Postgraduate Award (Australian Government, Department of Indus-
try, Innovation, Science, Research and Tertiary Education) Scholarship to
assist her in undertaking her PhD studies.
Gretchen Ennis is a Lecturer, Social Work and Community Studies Theme, School of Health,
Faculty of Engineering, Health, Science and the Environment, Charles Darwin University,
Northern Territory 0909, Australia.
Deborah West is an Associate Professor, Director of Education and Training Development,
Office of Learning, Teaching and Community Engagement, Charles Darwin University,
Northern Territory 0909, Australia.
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