Membership in both formal and informal networks has the potential to deliver positive outcomes for individuals and groups, however not all networks are equally effective. Several network characteristics such as number of social ties, the density of the network, the presence of leaders and how individuals are positioned within the network can influence performance. Further, a single type of network is unlikely to be effective in all situations. For instance, one analysis of social networks in Stockholm found that a network with a core group of heavily connected members surrounded by a periphery of sparsely connected members, facilitated collective action on a local level whilst simultaneously preventing collaborative management at a regional level.
Participants at the CEED workshop came from the University of Queensland, University of Melbourne, James Cook University, University of Western Australia, RMIT, University of Tasmania, CSIRO and the Stockholm Resilience Centre. Jointly organized by researchers from UWA and UQ, the workshop explored the theory, methodology and strengths and weaknesses associated with the application of social network analysis (SNA) in natural resource management.
“Our discussions revealed the importance in considering the value of information obtained from social-network analysis relative to the costs associated with data collection and the risks associated with poor response rates,” says Courtney Morgans, one of the convenors of the workshop.
“Reasonable justification also needs to be given as to how the network of interest will be bound. For example, is it more appropriate to bound the network at an institutional level or a geographic region? Will it be feasible to obtain a comprehensive dataset from all members of the population at this level?”
In addition to these practical considerations, the workshop explored theoretical assumptions relating to the position of the social network on the causal pathway: does the social network shape management effectiveness or is it that social processes shape the social network.
Social networks can be used in multiple ways, from simply describing a system, to understanding the processes that drive the formation of a system, through to informing analysis for improved decision-making. How social network analysis can be best used to inform practical recommendations for NRM will form the focus of several upcoming papers.
Image: Workshopping social network analysis