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Using social network analysisin community development

practice and research: a

case study

Gretchen Ennis* and Deborah West

Abstract In 2010, we proposed that integrating social network analysis into

community development practice may be a useful way to make overt the

links between micro- and macro-level issues in communities, and for

researching the impacts of community development work [Ennis, G. and

West, D. (2010) Exploring the potential of social network analysis in

asset-based community development practice and research, Australian

Social Work, 63 (4), 404–417]. This article presents research drawn from

a community case study and provides a real example of how network

analysis can be embedded in community development processes. The

research demonstrates that social network analytic techniques can be

useful in a range of ways, including: facilitating a critical analysis of ‘the

community’; focusing community work processes; and providing

particular understandings about the outcomes and impacts of

community work. In summary, the findings demonstrate that social

network analysis is a useful tool for facilitating community developmentand 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 permissions, please email: [email protected]

doi:10.1093/cdj/bss013

Advance Access publication 10 May 2012

40 Community Development Journal Vol 48 No 1 January 2013 pp. 40–57

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connected and therefore is a way to consider social structures of

various kinds.

Social network analysis and theory (with its links to social capital ideas)

has been discussed by a range of community work authors who have

articulated network approaches to community development (for example:

Trevillion, 1992, 1999; Gilchrist, 2000, 2004, 2009; Hardcastle, Powers and

Wenocur, 2004; Gilchrist, Bowles and Wetherell, 2010). Such authors have

argued that building and maintaining positive connections between

diverse groups of people and organizations can facilitate dialogue and

open up access to resources, information and ideas. Extending these

ideas, we have argued that integrating social network analysis techniques

into community development practice and research (particularly strengths

and network approaches) may assist in better understanding the processes,impacts and efficacy of community development work (Ennis and West,

2010).

Social network analysis is concerned with examining social structures.

As we have previously discussed:

Within social network theory, social structure can be conceptualised as a

network of social ties or relationships (de Nooy, Mrvar and Bategelj, 2005).

A social network is social structure which consists of two elements; these

are generally known as actors (or nodes or points) and ties (sometimesreferred to as links or relationships) (Ennis and West, 2010, p. 408).

Thinking in terms of the connections between people, groups and organiza-

tions can assist workers and communities to focus not only internally on

their communities (and the strengths and resources within them) but exter-

nally to consider the links to broader social structures that impact them

(Ennis and West, 2010). Drawing on the work of sociologists such as

Bourdieu (1977, 1986) and Giddens (1984), a network focus can provide

understanding about how our micro-level relationships combine to createand/or challenge broader social structures. Such an understanding of

the patterns of links and flows in smaller scale personal interactions can

assist in critical thinking about how these interactions may either reproduce

or challenge larger scale oppressive social systems.

We have previously proposed a range of ideas for the use of social

network analysis in community development work (Ennis and West,

2010). The current article provides a discussion of the use of one of those

ideas: the analysis of a participant network, before and after a communitydevelopment project. This analysis is drawn from research undertaken by

Gretchen (Ennis, 2011) as part of a larger case study. The case used is a

project undertaken by a grassroots, volunteer-based community network

called Ludmilla Neighbourhood Connections (LNC). LNC embraced a

Social network analysis in community development practice and research 41

a t T h e A u s t r a l i a n N a t i on a l Uni v e r s i t y onM a y2 6 ,2 0 1 3





































‘strengths’ or ‘assets’ approach to community development. Such an

approach highlights and mobilizes community strengths in working

towards meaningful change (Kretzmann and McKnight, 1993). The creation

and maintenance of positive relationships is a critical element of the

approach, as such relationships are viewed as ‘assets’.

Background

LNC: the ‘case’

The case in question was a community project located in a suburban neigh-

bourhood in Darwin, Northern Territory, Australia, which took place

between January 2009 and July 2010. The project involved the formationof a community network comprised of citizens from Bagot Community

(an Aboriginal community, located within the suburb of Ludmilla) and

other parts of Ludmilla1 as well as representatives from a range of local gov-

ernment and non-government organizations.

The LNC network formed as a result of long-term issues concerning the

social separation of Aboriginal and non-Aboriginal people in the area. This

separation is complex and multi-faceted, beginning with colonization and

reinforced by subsequent government policies which at various times ac-

tively sought separation of different cultures. Of the approximately 1700

people that live in the suburb, 430 are Aboriginal and 252 were born over-

seas (Australian Bureau of Statistics, 2007), with the balance identifying as

non-Aboriginal, Australian born residents. The majority of Aboriginal resi-

dents live in Bagot Community.

Gretchen was part of the formation of the LNC network in 2007 and took

on the role of facilitator as part of her PhD studies. The project primarily

relied on the work of volunteers and the in-kind support of the organiza-

tions involved, with some small community grants to undertake particularactivities.

The primary aim of the project (developed by the people involved) was to

increase supportive social networks between people of different cultures in

the neighbourhood and to broadly ‘create a sense of community’ in the area.

Participants agreed that the primary resources in the community were the

people: their knowledge, culture, skills and commitment to the area.

Other resources or assets identified by participants were focused upon

the natural environment, local school facilities and the passion and

resources of a range of individuals and community organizations in the

local area.

1 The participants in this study have indicated that the communities can be named.

42 Gretchen Ennis and Deborah West






































Social network theory

Theoretically, the aim of increasing supportive social networks is linked to

ideas from social capital theory:

The links between individuals and organisations, are key to sharing of information and resources, and mobilisation for change. Social networks

are a central concept in social capital literature, and are generally

considered to be the ‘structure’ within which social capital can exist

(Bourdieu, 1986; Putnam, 1993; Lin, 2001; Stone, 2001). (Ennis and West,

2010, p. 408)

Based upon the assumption that there were few relationships linking

people in Bagot Community and people in the rest of the suburb, the

LNC project focused on developing links of communication and dialogue.

These types of relationships have been called ‘bridging ties’ in social capital

literature (Putnam, 2000; Healy and Hampshire, 2002).

In order to ‘build bridges’, a range of activities were undertaken. Over

nineteen months, LNC held ten community meetings involving thirty-one

individual community members, three schools, a youth arts organization,

four non-government community/welfare organizations, a church group,

two local environment groups, members of local council and a member

of the Northern Territory government. Through these meetings, LNC orga-

nized a number of events and activities: gardeners’ mornings, a guided bushwalk and a family fun day, neighbourhood breakfasts, Christmas gath-

erings, a large public information meeting and a large community DVD

launch celebration. We also worked in partnership with other local organi-

zations on various community events, including the development of an

‘edible garden’ project and the production of a local neighbourhood

DVD. LNC also put together and distributed thirteen editions of a neigh-

bourhood newsletter to over 400 households and developed an online infor-

mation network via email and social networking sites.

As per a strengths philosophy, these activities and events were focused

on sharing empowering stories, understanding diverse local histories, iden-

tifying and highlighting neighbourhood assets and linking people and

organizations to achieve the aims of the project (Kretzmann and McKnight,

1993; McCashen, 2005).

Methodology

In order to understand changes in community networks, a pre- and post-

project network analysis design was employed for the research. The

network analysis software, Pajek (de Nooy, Mrvar and Bategelj, 2005),







































was used to develop the diagrams and network frequency distributions

presented here.

Collecting network dataThe LNC project targeted the neighbourhood as a whole; however, the

social network analysis was used to gain an understanding of the relation-

ships among active project participants and their local networks at the be-

ginning and end of the project.

A snowballing technique provided data about relationships (as people

only referred others they knew) and demonstrated who was connected to

the LNC project via the LNC members. We called the network of active

LNC members and their contacts in the neighbourhood the ‘LNC commu-nity network’.

To gather the snowball sample, we began with ‘active’ participants

(people attending meetings or communicating with the facilitator regular-

ly) and asked them to refer other people they communicate with in the

area who might agree to be interviewed. Participants were asked if they

would call this person ‘close friend or family’; if so, the relationship was

registered as a ‘strong tie’, if not it was registered as a ‘weak tie’. At the

end of this data collection process, information about actors and the

‘strength’ of their communication relationship was available for analysis.This technique provided a snapshot of the LNC community network at a

point in time (December 2008). There were forty-nine participants in this

pre-project network.

The same process of snowball sampling occurred after the project ended

in August 2009. The post-project network was made up of sixty-one people.

Only thirty-two of the forty-nine people in the pre-project network were

present in the post-project network. This is discussed in more detail later.

Analysing network data

Because we were interested in understanding cross-cultural social connec-

tions, the focus of this particular study was upon network structure and

composition. The structure of the network includes network size, connect-

edness of the actors, concentration or dispersion of actors, accessibility of

the network, degree of clustering in the network and the heterogeneity or

homogeneity of the actors (Wasserman and Faust, 1994). As this project

was aimed at increasing connections between different cultural groups,the various cultural groups identified by the participants are the attribute

included on these diagrams and analysis. For the analysis presented

here, the diverse cultural groups have been clustered into people who







































identify as ‘Aboriginal’, ‘born overseas’ and ‘Australian, no other cultural

group’.2

In terms of network composition, it is useful to consider how reflective

the LNC community network is in terms of the broader suburb. Network

composition data have been added to the diagram legends for both the

pre- and post-project participants.

Findings

Network diagrams were generated using the Fructerman Reingold energy

command for creating drawings in Pajek (de Nooy, Mrvar and Bategelj,

2005). The results of the pre- and post-network project network analysisare presented in a diagrammatic and descriptive statistical form.

The LNC participant network is not particularly reflective of the cultural

diversity in the suburb of Ludmilla. Twenty-five percent of the population

of Ludmilla identifies as Aboriginal Australian; however, in the LNC

participant network, only 10 percent identifies as Aboriginal Australian.

In terms of people born overseas, the LNC participant network almost

exactly reflects the 14.8 percent of people in Ludmilla born overseas. The

cultural diversity of the LNC participant network is reflective of the

suburb in terms of people born overseas, but not in terms of AboriginalAustralians.

The elements of interest in terms of network structure are network size

(the number of actors and the number of ties); the components of the

network (the sub-groups or sections of the network) and their linkages;

and the cohesion of the network, which is measured via the average

degree (number of connections) of network actors.

In terms of size, there are forty-nine actors joined by sixty-one ties in the

pre-project participant network. It is generally useful to explore the dia-grams to see if there are any components (or subgroups) because, as de

Nooy, Mrvar and Bategelj (2005, p. 61) discuss:

Social networks usually contain dense pockets of people who “stick

together”. We call them cohesive subgroups and we hypothesize that the

people involved are joined by more than interaction. Social interaction is

the basis of solidarity, shared norms, identity, and collective behaviour, so

people who interact intensively are likely to consider themselves a social

group.

2 The authors acknowledge that such clustering can serve to ‘make invisible’ distinct cultural groups.

The original analysis, used in the first stage of the community work, included the multiple cultural

groups as they were identified by participants. However, for the sake of visual clarity, the diagrams in

this article are clustered.







































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.







































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.







































The pre-project analysis shows a community network that is not particu-

larly cohesive, and is separated into three distinct networks. While it is on a

small scale, this ‘separation’ of Bagot Community participants from the ma-

jority of participants from the dominant cultural group is reflective of the

broader social separation in the neighbourhood.

Figure 2 shows the result of the post-project analysis.

When compared with the pre-project diagram, the post-project diagrams

show that in terms of cultural diversity, this network is becoming more re-

flective of the broader neighbourhood. In the post-project network, Abori-

ginal participants had increased by 3.11 percent (to 13.11 percent of

participants). This is still quite a way from 25 percent, but it is a positive in-

crease in nineteen months.

In terms of people born overseas, there is an increase of 2.39 percent in thepost-project network (to 16.39 percent of participants). Given that 14.8

percent of the population of Ludmilla was born overseas, LNC can claim

good representation in this respect.

The size of the post-project participant network is 61 actors with 102 ties.

This is an increase of eleven actors and forty-one ties (or new relationships)

Figure 2 Structure diagram of the post-project research participants. Actors ¼ 61. Cultural groups:

black identifies as Aboriginal (8 people, 13.11 percent of network); white, part of cultural group

‘born overseas’ (10 people, 16. 29 percent); grey, ‘Australian’ and no other cultural group (43

people, 70.15 percent). Tie strength: thin line, weak tie; thick line, strong tie.







































when compared with the pre-project participant network. However, only

thirty-two of the people in the pre-project network are present in the post-

project network. Seventeen of the people in the pre-project network were no

longer in the network by the time of the post-project data collection, and

there were twenty-nine new people in the post-project network. Seventeen

is a significant number of people to ‘drop out’ of a network. Further inves-

tigation revealed that nine people had left the area (reflecting the high

population turnover in the Northern Territory), three experienced personal

issues and five were unable to be contacted.

In terms of network components, there is now one connected network, as

opposed to three distinct networks visible in the pre-project participant

diagram (Figure 1). To further consider network connectedness or cohesion,

it is useful to again look at the average degree of the actors in the network.Table 2 provides a frequency distribution of degree and shows us that,

in the post-project participant network, there is an average degree of 2.98.

That is, on average, each actor is connected to almost three other actors.

There has been a small increase in average degree (of 0.61) from the

pre-project participant network which had an average degree of 2.37.

Also notable is that actor ‘v1’ has gained more connections (sixteen con-

nections, or five more than in the pre-project participant network), and has

far more connections than the next most ‘well connected’ person (actor

‘v21’, who has seven connections). Thus, actor ‘v1’ is an actor to ‘keep an

eye on’ in terms of power and influence in this network, and also in

terms of holding the network together.

Table 2 Distribution of the degree of pre-project research participant frequencies

Degree Frequency Frequency

percentage

CumFreq CumFreq Representative

1 14 22.9508 14 22.9508 v8

2 20 32.7869 34 55.7377 v11

3 11 18.0328 45 73.7705 v2

4 4 6.5574 49 80.3279 v14

5 4 6.5574 53 86.8852 v3

6 6 9.8361 59 96.7213 v4

7 1 1.6393 60 98.3607 v21

16 1 1.6393 61 100.0000 v1

Sum 61 100.0000

Sum 182.0000000

Arithmetic mean 2.9836066Median 2.0000000

Standard deviation 2.3434023

Actors: 61; lines: 102; density: 0.0497268; the lowest value: 1; the highest value: 16.







































Increased connections can be seen in the post-project network. In the

post-LNC project participant network, 22.95 percent were connected to

only one person, whereas in the pre-project network, 38.76 percent had

only one connection; therefore, more people had more connections in the

post-LNC project network.

It is quite clear in Figure 2 that while the previously ‘cut off’ component

of Aboriginal residents from Bagot Community is now connected to the

broader network, it is a fragile link. The links between the cluster of Abori-

ginal cultural group actors and the broader network are to only three other

actors, actors ‘v21’, ‘v61’ and ‘v1’. While five connections have been made

that did not previously exist, more are needed to strengthen the network.

The ‘X-street’ component in the pre-project diagram (Figure 1) has

changed dramatically, with two actors no longer in the network [23 and38] and the remaining two actors [44 and 27] quite well linked into the

network.

In summary, some significant differences between the pre- and post-LNC

project networks can be seen. The post-project network is larger, with more

actors and more connections between them; it is also slightly more cohesive

and there are bridging ties evident between various clusters in the network

that were not seen in pre-project diagram. The LNC participant network has

also become more representative of the various cultural groups in the

neighbourhood.

Discussion: using network analysis in communitydevelopment practice

A meaningful sample population to ‘measure’

‘Community’ is difficult to define as there are multiple meanings and uses

of the term embracing vastly different philosophical and political values

(Young, 1990; Lynn, 2006). There are often assumptions about community being a universally positive thing, with little reflection upon whose under-

standing of community is being touted. Aside from defining communities

as those ‘of interest’ or those ‘of place’, much community work literature

and research does not clearly define the community it is concerned with.

Drawing a sample from a ‘community’ then also becomes problematic.

As previously explained, asset and network models of community devel-

opment place high value on relationships. The snowball sample technique

is in itself a useful way to gain an understanding of the relationships between people who are involved with the project, and their communica-

tion networks in the neighbourhood. The networks that are ‘revealed’ via

the diagrams provide information about a new network being created

within the neighbourhood. This is useful for understanding the ‘assets’







































LNC can currently, and potentially, access, and we are able to see the ‘reach’

of the LNC into the neighbourhood via direct relationships.

Using network diagrams to focus practice

Almost all community development literature emphasizes the importance

of linking up, and building networks. Similarly with this project, there

was an emphasis on locating, acknowledging and joining up the various

people, programmes and organizations operating within, or providing ser-

vices to, Ludmilla. A network focus, including the use of the network dia-

grams, assisted in being more strategic in the networking activities.

Network analysis has been proposed as a useful resource for practice and

research by a range of social work and community development authors

since the 1980s (for example, McIntyre, 1986; Seed, 1990; Folgheratier,2004; Gilchrist, 2004; Hardcastle, Powers and Wenocur, 2004; Kirke, 2009;

O’Connor et al., 2006). Yet, there has been little research aimed at exploring

its use in community practice. For LNC, social network diagrams

helped to provide a sense of strategy to the ‘linking up’ aspect of the

community work.

Network diagrams were used twice in practice with LNC members. This

was because network diagrams were only generated twice (before and after

the project). At the outset, the diagrams helped LNC to explore and thinkabout the network we were working with. The initial pre-project social

network diagrams contributed to the LNC’s ‘network thinking’, through

a visual representation of who was involved and linked to the LNC

network. This provided an opportunity to think-through who was and

was not in the network and how people within it were linked. The pre-

project diagrams showed that while participants from Bagot Community

were connected to each other, there were no connections to others in

Ludmilla. This suggested a lack of bridging connections in social capital

terms. LNC members were able to consider the causes of the networkstructure, the implications and what might be done about it.

The facilitator encouraged LNC participants to consider new connections

as opportunities for dialogue and activity. Attempting to get people into the

same space and perhaps fostering some understanding about each other

was a basic goal of many of the activities. New connections forged

through organizing and/or attending various activities enabled partici-

pants to share knowledge and culture.

When the post-project diagrams were first drafted, they were discussedwith LNC members at various formal and informal meetings. A community

presentation of all the results of this case study, including network

diagrams, was also given in March 2011. The comparisons between the

pre- and post-project diagrams provided people with clear evidence of







































the formation of a more connected and growing LNC network. This infor-

mation, combined with other (qualitative) data, was a great way to visualize

and understand some of the impacts of the project on individuals and on

the network structure.

Through integrating the use of network diagrams into the community

work, we were able to take network approaches to community develop-

ment a little further by using network analysis as a tool for practice. The

network ideas linked nicely to the strengths approach in terms of focusing

on what the community has rather than what the community needs (Kretzmann

and McKnight, 1993) and the network diagrams provided a focus for

linking up those identified assets (including people and their culture).

The social network diagrams and analysis were very useful in terms of

better understanding the need for bridging ties, and being able tomeasure the development of these.

Using social network diagrams to facilitate critical thinking

One of the key criticisms of asset and network approaches to community

development is their lack of useful frameworks for working with difference

or oppression in communities (Healy, 2005, 2006; Curtis, 2010). This

criticism has real relevance to the project discussed here. While the

project facilitator respected diversity and difference, some participantsdid not. Very different political and philosophical views were expressed

by participants – some were blatantly racist and aimed at assimilating all

cultures into the dominant (‘white Australian’) one. These views reflected

broader issues in Darwin, Australia, specifically around colonization and

(perhaps unconscious) attempts to ‘homogenize’ the community in order

to make it more cohesive.

The social network diagrams opened up discussion and were used to en-

courage critical reflection upon difference, and how processes of coloniza-

tion might be impacting our local-level relationships. Projects with goalsof community cohesion can sometimes focus upon ‘sameness’ and suppress

differences, while asserting ‘the need for unity based on the integration of

different cultures and experiences within society’ (Gilchrist, 2004, p. 53).

This may serve to enforce the norms of one (more dominant) group on

the other groups, resulting in new connections simply reproducing the so-

cially unjust aspects of society that already exist. Australia has a troubled

history of government policies aimed at the assimilation of Aboriginal

people into mainstream society, and the LNC project had to be very waryof potentially colonizing practices.

In this research, we found that building cross-cultural group contact can

be considered a strategy for addressing deep-seated racisms at a local rela-

tionship level. Through the construction of social bridges, and simply







































attempting to ‘get people into the same space’ (either physically or psycho-

logically), the LNC could open up the beginnings of a dialogue aimed at

understanding rather than influencing. This required specific facilitation

skills (such as mediation, and community education) to assist in addressing

some existing power imbalances. In many ways, this was the most challen-

ging aspect of the project. However, through using a range of ‘linking up’

tools that also sought to promote diverse views and understandings of dif-

ferent groups in the area (such as a neighbourhood newsletter and a neigh-

bourhood DVD), LNC was able to start the fragile process of creating

a new, more empowering narrative about the different cultures in the

neighbourhood.

Using network analysis to understand project outcomesIn terms of measuring the outcomes of the project in line with its aims to

increase social connections across diverse cultural groups, the network ana-

lysis showed that, on average, connections have been increased.

Social network analysis also provided a method for understanding the

cohesiveness in the LNC network. While there were slight increases in

the cohesiveness of the LNC network over the nineteen-month time

frame, none of the networks are particularly cohesive. This is not surpris-

ing, however; as other literature has demonstrated, communities withdiverse groups of people who have little in common with one another are

rarely highly cohesive (Cheong, 2006; Jaffe, 2006; Letki, 2008). What is im-

portant is that new links have been formed between diverse groups, and

these open up opportunities for information and other resources to flow

between groups where none previously existed.

Social network analysis was useful in demonstrating structural change in

the LNC network over the nineteen months of the project. Compared with

other qualitative methods (that were used in the broader case study), the

network analysis provided a more ‘zoomed out’ view that allows the re-searcher to step back and consider how relationship changes translate

into structures.

Such analysis provides a different kind of understanding about commu-

nity work outcomes. Knowing what participants think about a programme

is important, but network analysis allows the exploration of changing com-

munity structures. We believe that this adds both depth and focus to other

evaluative methods.

Social network analysis is not so much interested in aggregates of actorattributes, but in the relationships between actors. The focus is not on indi-

viduals, but on relationships. The social network analysis has provided a

measure of the relationships in the network prior to, and after, the project.

Such an analysis can shed light on how the relationships between people







































in the LNC networks reflect and/or reproduce wider social structures. The

new connections between Aboriginal and non-Aboriginal people in the

LNC can be viewed as a positive change, facilitating dialogue and

opening up new opportunities and resources in terms of cross-cultural

understanding for all those involved. These new connections can also be

viewed as a disruption to the disempowering history of separation

between Aboriginal and non-Aboriginal people in the broader suburb

traditionally.

The limitations of social network analysis in community development

Social connections are not always positive, they can serve to oppress and

reproduce dominant and unjust ideologies and systems (Bourdieu, 1986;

Portes and Landolt, 1996; Wilson, 2005). As others have discussed, socialnetwork analysis cannot provide an understanding of culture, or human

agency (Wellman, 1983; Emirbayer and Goodwin, 1994), and their influence

upon communities. We too believe that important understandings about the

meaning of community networks, and the dynamics of power, culture and

history operating within them, must come from combining social network

analysis with more qualitative methods.

As discussed previously, this network analysis was only one of multiple

methodologies embedded with a case study framework used to exploreand understand the processes and impacts of the LNC project. What we

hope to have demonstrated is that network analysis enables us to do some-

thing that other methods cannot, that is, to capture snapshots of social struc-

tures. These snapshots allow us to consider what exists in terms of the links

and ties between people in a given network at a particular point in time,

and to subsequently understand changes over time. Network analysis can

assist in exploring the way we create and are created by social structures.

Conclusion

Undertaking social network mapping can provide useful information about

community network structure which communities can ‘work with’. Evalu-

ation of community projects can be more comprehensive and meaningful if

changes are understood in a range of ways. We have argued that changes in

community relationships and structure can be measured meaningfully and

effectively using social network analysis.

In summary, the integration of social network analysis into the commu-nity development project overviewed here assisted in understanding the

community we were working with and in helping to focus and inform

aims and practice of this project. The integration of social network analysis,

as a tool for assisting network thinking, provided a strong link between







































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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Documents

Community Dev J 2013 Ennis 40 57