Who’s in the know’ – using social network analysis to support adaptive communities

1. 1
“Who’s in the know” - using Social
Network Analysis to support adaptive
communities

2. NSW Adaptation Approach
2
Regional
Vulnerability
and
Assessments
Stakeholder
Engagement
& Capacity
Building
NSW
Relevant
climate
Information

3. www.ClimateChange.environment.nsw.gov.au

4. Regional Engagement
People engaged –
600+
Pop. represented –
73%
LGA’s covered – 61%

5. Building Adaptive Capacity
Providing tools and
resources to minimise
impacts of climate change in
local communities
Including grants…..

6. Building Resilience to Climate Change grants
 Grants of between $15,000 - $80,000 are available to respond
to a previously identified climate change risk or vulnerability,
via:
- climate change risk assessment, meeting Australian standards; or
- a climate change vulnerability assessment (peer reviewed
methodology)
 Round 2 focus on proposals that
- Address water supply or security
- Adapt priority infrastructure
 Collaboration with councils,
regional organisations, researchers,
private sector is encouraged.
 www.lgnsw.org.au/policy/climate-change/building-resilience

7. Adaptation Research Hub
$2.75 million leverage fund
generating $6 million in
collaborative research over 3
years in key research areas:
 Biodiversity – Climate Futures
at Macquarie and CSIRO
 Adaptive Communities –
Institute for Sustainable Futures
and CSIRO
 Coastal processes and
responses – Sydney Institute for
Marine Science and ACCARNSI

8. 8

9. 9
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Social networks
A social network is a social structure made up of a set of
actors (such as individuals or organizations) and a set ties
between these actors
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10. Benefits of Social Networks
 More flexible than top-down
communication strategies.
 Information is likely to be
trusted and accepted.
 Information can spread
quickly (e.g. social media).
 But, very limited evidence or
proof of their application.

11. Social Network Analysis
 People/Entities are represented as nodes.

12. • People / Entities are represented as nodes.
• Connections are represented as edges/lines.
Connections may be kin,
work, acquaintanceship,
friendship, co-authorship,
knowledge etc.
SNA Allows for analysis using
mathematical graph theory
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13. Social network analysis

14. Data Sources
Archival Data
Ethnographic / Interview Data
Historical Data (e.g., meeting minutes)
Survey Data
Social Media (e.g. Twitter feeds)
SNA Software (examples, many options)
UCINet
KeyPlayer

15. 1
5
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16. Describing the structure of social networks
Centrality - Density - Betweeness
Centrality:
 How many ties a specific node has.
 A high degree of centrality occurs when an
individual has considerably more ties with
other actors than other individuals within the
networks.
 These ‘highly connected’ individuals are
important for the diffusion of information
throughout the network.1
6
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17. Density (a measure of cohesion):
 the number of links divided by the number of
nodes in the network.
 density of a networks typically grows over
time, as individual actors increase their
interactions
 networks exhibiting a high density may
contribute to the strengthening of trust
between individuals and/or groups and
thereby also increase the possibility for
social control
 high density may also benefit the spread of
information throughout a network by
increasing the accessibility of information

18. Betweeness:
 the extent to which each node contributes to minimizing the
distance between nodes within the network.
 That is, this measure can be used to identify the actors that
contribute most to linking the network.
 These actors are critical to ensure shared learnings and
cooperative action.
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19. Adaptive Communities Node Case study
Aim
To look at the process by which science, policy
and communities interact by developing an
understanding of how formal networks of
stakeholders interact with informal networks to
convey information at the local scale.
Goal
To understand how decision-makers can better
engage with communities to improve to
acceptance and uptake of climate adaptation
policies/programs/strategies?

20. Shoalhaven Council
 Encompasses 4,531km2 including
national parks, state forest,
bushland, beaches and lakes.
 Population: 97, 694 people with a
density of 0.22 people per 0.01km2
(ABS, 2013).
 Main sectors of employment are
manufacturing, government
(including Defence), retail and
tourism.
 Rural land primarily dairy farming,
nurseries, and a growing number
of more intensive agricultural
activities.
 Strong cultural history with links
to indigenous communities, the
Wodi Wodi and Wandandian
Aboriginal people.
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21. Methods
 Qualitative Social Network Analysis (semi-
structured interviews)
 Where do you get your climate
information?
 Who do you share climate information
with?
• Participants identified through purposive
snowballing
• 24 participants were surveyed:
 12 from government agencies (formal
networks)
 12 from key climate community
groups/members (informal networks)
2
1
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22. Results:
Where do you get your climate information
 24 participants identified 165 ‘entities’
 45 government entities (local, state and/or federal)
 25 community based organisations
 23 mass media entities (e.g.- tv, radio, newspaper)
 16 ‘other’ (e.g.- mother, father, neighbour, etc.)
 14 Non-government organisations
 12 mass communication channels (e.g.- internet, mobile)
 12 international entities
 6 research organisations
 5 social media outlets
2
2
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23. Results:
Where do you get your climate information
2
3
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24.  Each node had ties to
2.5 alternative nodes
(average)
 Three key players:
 Bureau of
Meteorology (#6)
 ABC Radio (#14)
 Sydney Morning
Herald (#76)
• 84.2% coverage (n=139
distinct persons

25. Results:
How do you share climate information
 24 participants identified 194 ‘entities’
 79 Community based organisations
 47 Government (local, state or federal)
 32 Other (father, mother, neighbour, etc.)
 15 Non-government organisations
 7 mass communication (internet, mobile)
 6 mass media (tv, radio, newspaper)
 5 social media
 3 research organisations

26. Results: How do you share climate information

27.  Knowledge
disseminated in dense
clusters
 Knowledge primarily
shared with local
profession and
geographical group
 Network far more
fractious
 Three key players:
 Local radio and 2
community
members

28. Key findings
 Community members access climate
information from a wide variety of sources,
however….
 They don’t really share what they learn
 Only a few key players; Limited functional
redundancy??
 SNA works!!!

29. Implications
 SNA can be used to identify key
nodes/individuals to disseminate climate
information
 Provides OEH with critical information about
how to engage communities in climate
adaptation;
 Trusted source of information
 Broad coverage and quick (links with
emergency services)
• Potentially identifies cost effective means of
community engagement

30. In seeking to increase acceptance and uptake of climate
change and adaptation strategies/policies/etc;
• Build climate resilient and adaptive communities.
• Increase public safety (i.e. fires, storms, etc.)
• Social connectness /cohesion
• Economic benefits (i.e. industries sustained and/or
enhanced)
Benefits extend beyond climate to any area where
community engagement is important!!

31. What next?
 Upscale: how does this translate to other
areas/communities?
 Bega complete, 31 interviews, SNA
currently underway
 Another area (inland)
 Also SNA-ing the NSW Adaptation Hub
 Qualitative understanding: what drives
patterns?
 Finding efficiencies: what role for modern
technologies (social media, micro-sites, etc.)

32. Two reports on:
www.uts.edu.au/research-and-teaching/our-
research/institute-sustainable-futures/our-
research/major-projects/nsw
An Introduction to Social Networks for Engaging the Community in
Climate Policy.
A preliminary assessment into the utility of social networks for
engaging local communities in climate adaptation policy
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33. Social Network Analysis – Who’s who in climate
and water communication?
Participate in a SNA
Send an SMS with content
NSWOEH
to
0427 541 357
Normal SMS charges apply. Your number is not
stored or given to any 3rd parties
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40. ACKNOWLEDGEMENTS
 Research Team
- Chris Cvitanovic
- Rebecca Clunn
- Thomas Measham
- Brent Jacobs
- Anne-Maree Dowd
- Ben Harman
 OEH, in particular Chris, Storm, Polly
 Natasha Kuruppu and Sam Sharpe
 Shoalhaven city council
 All of our participants

41. www.climatechange.environment.nsw.gov.au
Heather.Stevens@environment.nsw.gov.au
Suzanne.Dunford@environment.nsw.gov.au