'Who's in the Network?' When Stakeholders Influence Data Analysis

Christina Prell, Klaus Hubacek, Claire Quinn, Mark Reed

Research output: Contribution to journalArticlepeer-review

90 Citations (Scopus)

Abstract

Environmental applications of social network analysis (SNA) are just beginning to emerge, and so far have focussed on understanding the characteristics of social networks that increase the likelihood of collective action and successful natural resource management. We move beyond this discussion to demonstrate how knowledge gained from analysing the social networks of stakeholders can be harnessed for selecting stakeholders, and further, how these analyses can be influenced by the expressed wishes and concerns of stakeholders. Although we began our SNA using concepts derived from the resource-management literature, stakeholder involvement in the interpretation of the results led to the use of SNA techniques that had not previously been applied in the context of resource management. We thus re-analysed our data and modified our selection of research participants. Re-analysis led to the selection of research participants who (1) had unique positions in the network, thus occupying non-redundant communication roles in the network, (2) came from different stakeholder categories and (3) were relatively well-connected to others and tended to broker across different segments of the network. By combining insights from researchers and stakeholders in this way, it was possible to use SNA in an innovative and sensitive way to better meet the needs of the stakeholders and the research project.

Original languageEnglish
Pages (from-to)443-458
Number of pages16
JournalSystemic Practice and Action Research
Volume21
Issue number6
DOIs
Publication statusPublished - Dec 2008

Keywords

  • Social network analysis
  • Social learning
  • Peak District National Park
  • Resource management
  • Participatory approaches
  • resource-management

Fingerprint

Dive into the research topics of ''Who's in the Network?' When Stakeholders Influence Data Analysis'. Together they form a unique fingerprint.

Cite this