Social network analysis

Submitted by Sukaina Bharwani | published 28th Mar 2012 | last updated 18th Dec 2020

Climate Adaptation Training Annotation

  • Level: Advanced 
  • Time commitment: 1-2 hours 
  • Learning product: Tool/method summary 
  • Sector: Multi-sector 
  • Language: English 
  • Certificate available: No 


Social Network Analysis (SNA) analyses social networks and institutional actors (organizations, individuals, interest groups, etc.) and their linkages (socio-institutional relationships), mapping the influence and the exchange of information to assess adaptive capacity.

This module aims to provide background to socio-institutional network mapping, the characteristics of such networks, guidelines on conducting the exercise and examples of where it has been applied.

*Download the technical brief from the right-hand column.

Background to the method

A number of methods are emerging that can identify the various actors (or stakeholders) involved in decision processes, and map out these linkages. These can be represented (visually) and analysed with network maps. These can be further analysed, in qualitative (step-by-step guide) or quantitative terms using social network analysis. The background and key benefits of the approach are provided in Box 1 in the technical briefing note. Participatory social network mapping and analysis reveals insights about the substance of these relationships by making explicit the types of flows between actors (e.g.information, money, advice, policy, etc.) and the perceptions of influence and power in the network.

Quantitative SNA provides a variety of measures/indicators to help describe the overall relational structure of a social network, as well as the roles of individuals within it. SNA can provide insights which can then be explored further with other methods, notably follow-up interviews, statistical analysis, agentbased modelling and participatory scenario creation. SNA can be undertaken using qualitative or quantitative methods. The main difference is that quantitative SNA graphs are ‘whole’ networks rather than qualitative egocentric networks based on the perception of (usually) just one actor. They are also more comprehensive (i.e. more nodes and links) and can be quantitatively analysed with SNA software using standard statistical tests.

Strengths and weaknesses

The main strength is SNA provides a formalised method to visualise stakeholder and knowledge networks, and in doing so, to understand them in the context of future action. It provides information on institutional actors and relationships, their decision framing, and the influence and exchange of information for progressing adaptation and overcoming barriers. It can also relate these quantitative metrics and use these to benchmark progress towards outcomes. Qualitative SNA is quick and relatively easy to do and encourages participation across diverse viewpoints and actors. Quantitative SNA extends to provide correlations on key variables to further understanding. 

The potential weaknesses involve the subjective bias, including participation bias for qualitative SNA, and the high survey size and time needed for quantitative SNA. Quantitative SNA can also be a time-consuming and intensive process. Furthermore the method does not include a temporal or spatial dimension, and the Networks can have artificial boundaries. 

Added value of the tool for the field of climate adaptation

The approach has high relevance for adaptation. It builds on the growing consensus that adaptation is a process, i.e. that implementing adaptation involves more than a set of technical options. There are important barriers to adaptation involves more than a set of technical options. There are important barriers to adaptation that are part of existing socio-institutional processes and these can be revealed and subsequently negotiated through SNA. It can also investigate the evaluation of uncertainty, i.e. how decisions are framed and the subsequent choice of appraisal tools. 

Where has this method been applied?

The first MEDIATION case study, focusing on Finland, used egocentric SNA to investigate farmers’ involvement in environmental conservation through their relationships with other actor types, i.e. with conservation stakeholders. The research was investigating the effectiveness (for the local ecology and economy) of agri-environmental schemes (AES), and their role as potential adaptation options in the context of future climate change. These schemes are an existing policy instrument for enhancing biodiversity in Finnish agricultural landscapes, promoting active management and maintaining the conservation values of semi-natural grasslands and other traditionally managed biotopes.

The second case study focused on Guadiana river basin, presenting an illustrative example of adaptation decision making in the agricultural and water sectors (see Varela-Ortega et al., 2014). This basin is expected to be one of the most seriously affected by climate change in Spain, with a potential decrease in water resources of 11% by 2030 and associated impacts on irrigated agriculture. A social network mapping exercise was undertaken to analyse the social and institutional framework of climate change adaptation. This was applied to a group of basin stakeholders: the water administration, representatives of the main irrigation communities, active environmental groups and the different climate change offices involved in the basin (National and Regional). The analysis focused on ‘how are climate change adaptation related decisions taken in the Guadiana basin, in the agricultural and water sectors?’

In addition to these MEDIATION case studies, SNA has also been applied in these situations:

Training Resources


Varela-Ortega, C., Blanco-Gutiérrez, I., Esteve, P., Bharwani, S., Fronzek, S. and Downing, T. E. (2014). How can irrigated agriculture adapt to climate change? Insights from the Guadiana Basin in Spain. Regional Environmental Change. DOI:10.1007/s10113-014-0720-y.

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