Social network analysis

How to change the pattern of resource flow relations to improve overall network outcome?

Social Network Analysis (SNA) maps and analyses social systems. Social systems consist of actors and their relationships. The actors can be people, groups, or organizations. They can also be referred to as nodes, network members, or players. SNA is an authentic systems technique, because it focuses on the pattern of relationships between all network actors rather than on the attributes of the individual actors or relations between pairs of actors. Improving the overall outcome of these patterns is the practical goal of SNA.

Relations (mentions in NGO progress reports) between NGOs in an area in Uganda (Williams and Hummelbrunner, 2010)

Resource flows  are key
In SNA the relationships between actors are studied in terms of resource flows, where resources can take the form of money, information, trust, advice, advice-seeking, assistance, support, materials, collaboration, referrals, or influence. These resource flows can be assessed in terms of quantity and direction, which in turn determines their importance. Nodes with above-average inflow or outflow of resources are often designated as key actors or major players.

Steps in SNA
Social Network Analysis for research or practical purposes follows a number of steps:

  • set a goal, enhance the outcome of certain resource flows.
  • identify the actors, i.e. the system boundary, using a fixed list or an open list. An open list builds on insider knowledge of network members to complete the list.
  • collect data, i.e. determine the relationships between actors. This may involve the use of a relational matrix. The type of resource flow relationship considered affects who is included.
  • visualize and analyse the data in terms of exclusion, participation, resource transmission, brokerage, centralization, density, and stability. This step may require dedicated software.
  • design a strategy to improve network outcome, e.g. an innovation strategy. SNA in itself does not produce solutions. Its contribution is to provide insight in network details and complexity.

The network approach to the study of behavior is guided by the mathematical theory of node-edge graphs (Freeman, n.d.). This has facilitated the development of software packages to visualize both. For those who are new to SNA, Clark (2006) has prepared a basic manual for the use of two packages, NetDraw©, which is free, and Ucinet©, which has a trial period of 90 days. Both can be downloaded from Analytic Technologies. Passmore (2011) presents a full overview of available software. In fairly uncomplicated cases or when quantitative analysis is not an issue, pen and paper or concept maps will do, too.

History and applications
Scott (1992) traces the origins of SNA to the 1930s when one group of sociometrists studied the diffusion of information, while two other groups of anthropologists developed the ideas of Radcliffe-Brown. The latter – influenced by Whitehead’s process philosophy – claimed that the fundamental units of anthropology (and by extension: sociology) were processes of human life and interaction. During the 1960s, the strands were united, after which the techniques were increasingly applied within social sciences fields, health and psychology (Clark, 2006). SNA is now part of mainstream social sciences (Marin and Wellman, 2009) and the International Network for Social Network Analysts (INSNA) has more than 1200 members. SNA has found important applications in organizational behavior, inter-organizational relations, and other practical fields, including rural development (Clark, 2006; Davies, 2009 ).

This post was generated using Joe Novak´s Cmap Tools (see earlier posts) and applying the main principles of Bob Horn´s structured writing. It was inspired by Chapter 3 of Systems Concepts in Action by Bob Williams and Richard Hummelbrunner.

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