Social Network Analysis
Social network analysis [SNA] is the mapping and measuring of relationships and flows of information between people, groups and organizations. The nodes in the network are the people and groups while the links show relationships or flows between the nodes. SNA provides both a visual and a mathematical analysis of human relationships. It is the relationships and ties between the different actors which are key in social network analysis 
‘Society is not merely an aggregate of individuals; it is the sum of those relationships in which these individuals stand to one another’ Marx 
A social network is ‘a set of relationships among actors’ (Mote 2007) and social network analysis (SNA) focuses on analysing the types and forms of relationships between social entities, as opposed to their characteristics per se. It is the study of social structure as created through social relations between people, groups, institutions and organizations and cross-scale interactions but also encompasses e.g. interactions with information, knowledge and social learning processing; power and political dealings or disease transmission patterns. SNA is a process of identifying, measuring and mapping these often informal relationship networks, where nodes in the network are the actors (people/groups/computers etc) while the links show relationships and/or flows of tangible or intangible resources between the them (Haythornthwaite 1996). These ties can consist of e.g. friendship, kinship, resource exchange, they can be one way or reciprocated, close or distant, and can overlap with other sorts of ties between and within a network. Different resources can ‘flow’ as a result of these differing relationships (knowledge, goods, services etc).
Therefore, information that is collected to construct a network model (map) of the social system includes a) the actors; and b) the links (defined by responses to the research question posed); c) the attributes of the actors and links (that do not originate from relations to a) and b)); and d) boundary conditions of the network determining inclusion and exclusion of actors (Cumming et al. 2010).
A basic social network map (sociogram)
Source: Valdis Krebs: http://www.orgnet.com/sna.html
In analysing networks, the locations of actors are evaluated and these measures provide insight into the types of roles and groupings in a network e.g. who are the knowledge holders or gatekeepers, connectors, leaders, bridges, isolates, where are the clusters and who is in them, who is in the core of the network, and who is on the periphery, with consequences for how the network ‘functions’ and the individuals within it behave.
SNA provides both a visual and a mathematical analysis of relationships, but its concern with the empirical investigation of social relations and social structures reflects its historical basis in sociology and anthropology. As such, developments in the analysis of social networks challenge distinctions between quantitative and qualitative analysis ‘to the point of suggesting a highly distinctive research orientation within the social and political sciences’ (Breiger 2004).
Specific Applications of SNA
SNA was used to identify, compare and characterize informal relations within/between individuals, organizations, institutions to model real-world interactions underlying knowledge sharing, social learning and decision-making processes as part of the SEI Google.org project. Among other aims, this approach highlighted formal/informal knowledge and social learning relationships: ‘who knows/shares/interacts with whom’; what types of information/ knowledge/ interactive resources support or hinder robust adaptive decision-making; what are the bottlenecks in information and knowledge flows for decision-making and how can these be improved to support social learning.
A review of several examples in the literature of using SNA to address natural resource management questions can be found following the SNA review summary page.
Some basic steps in conducting a SNA
- clarifying objectives and defining the scope of analysis (e.g. mapping a knowledge domain),
- developing the survey methodology and designing the questionnaire,
- identifying the participants (network) and providing justification for its boundaries if appropriate,
- collecting the survey data and gathering further information from other resources,
- analysing the data through formal methods of SNA,
- review of process and outcomes to identify problems/opportunities,
- design and implementation of actions to bring about desired changes,
- mapping the network again after an appropriate period of time
Relationship with Agent-based modelling methodology
There is a growing recognition of the importance of cross-scale interactions in NRM. SNA and agent-based modelling (ABM) both address the question of how localized interactions among social actors give rise to larger scale patterns or structures that may facilitate or constrain behaviour of actors. A recognised challenge of SNA is that measurement of the final form of networks does not reflect the dynamics that have led to their eventual formation. In the absence of longitudinal network data agent-based modelling can be a complementary method for investigating the interplay of social processes, leading to the understanding of emerging network structure (see Cumming et al. 2010).
Links to various tools useful for analysing and visualising networks:
GEPHI – The Open Graph Viz Platform : http://www.gephi.org
Analytic technologies: http://www.analytictech.com/networks/graphs.htm
Hanneman, Robert A. and Mark Riddle. 2005. Introduction to social network methods. Riverside, CA: University of California, Riverside (published in digital form at http://faculty.ucr.edu/~hanneman/)
International network for Social Network Analysis: http://www.insna.org/
Social Networks Journal: http://www.elsevier.com/wps/find/journaldescription.cws_home/505596/description#description
Breiger, R 2005 ‘Introduction to special issue: ethical dilemmas in social network research’. Social Networks 27: 89–93
Cumming G.S., Bodin O., Ernston, H and T. Elmqvist, 2010, Network analysis in conservation biogeography: challenges and opportunities, Diversity and Distributions, 16, 414-425
Haythornthwaite, C. (1996). Social network analysis: An approach and technique for the study of information exchange. Library and Information Science Research; 8:323-342.
Mote, J.E., Jordan, G., Hage, J., and Whitestone, Y. 2007. ‘New directions in the use of network analysis in research and product development evaluation.’Research Evaluation 16(3): 191–203.
- See a SNA case study from Bolivia here.
- See a SNA case study from Argentina here.
- See a SNA case study from Chile here.
- NetMap for government, donors etc in Kenya