Social Network Analysis and Complexity Theory in Practice
Case Study: the trinity session
Modern theory on all levels is enthralled and transfixed by the concept of networking.
In virtually all discourse regarding communication, organization, globalization, technology, and furthermore, in pure science, from biology to genetics and on almost ad finitum, researchers are turning their attention to the significance of the ways in which elements of systems interact.
Social network analysis is rapidly emerging as a powerful tool for the cultivation of effective and efficient networks. Concentrating on an assessment of the finite movements and functions of elements of the transfer of assets between nodes of a given network set, this type of analysis is interested in providing an understanding of how networks
Big business has already discovered the utility of such research, and has been using tools to uncover the ways in which information flows between employees and management. From email monitoring to focus groups, etc. many companies are racing to find a visual and tangible overview to how connections within their organization and between organizations function, in order to improve the efficacy and efficiency of those communications. Of course, within the context of economy and business, this inevitably means to increase profit and market share.
However, the same concepts as applied to any network group can be used not only to increase and/or effectively transfer material assets, but also to transfer other, non-material assets. Increasingly, network discussion turns its attention to the powerful and valuable asset of social capital; that is, the value of the shared knowledge and skill set of individual members, and the potential for transferring that capital to other members of the network.
In this way, network analysis can be a key factor in the cultivation of networks interested in cultural and social development.
While it may seem somewhat expansive to consider the ways in which the human immune system, for example, reacts to the introduction of a foreign body, and the way in which a social group reacts to a new member, the basic concepts apply on a fundamental level to both. In this sense, all network structures can be conceptualized in relation to ‘contagion’- in the biological example, the spread of disease or bacteria; in the social group example, the spread of rumor or information. In information theory or computer networking studies, contagion refers to the transfer of ‘memes’ (Laas, Culture Jam 2000) or contagious ideas, or more basically to the spread of computer viruses.
To take this concentration one step further is to consider a profoundly related field of research, and to examine the bridge between the two. Complexity theory, in the tradition of the BACH research group (see Burks, Axelrod, Cohen and Holland) and subsequently the subject of a myriad of scientific studies, explores the relationship between complex systems and adaptation. Networks, by definition, are necessarily complex adaptive systems, meaning that, at a fundamental level, they must change and adapt to survive outside factors. Failure to adapt to external influence ultimately results in the break down of the network.
This line of research is currently being applied to such varied foci as modes of cooperation, political strategy and peace keeping measures, and disease contravention.
To bring these concepts together, a truly thorough, in-depth analysis of the nature of any given network needs to combine not only a momentary snapshot of the interactions between nodes or network elements, but an understanding of the effects of the introduction of external influences over time, and the adaptive responses or residual effects of the adaptation to those forces. In this way, networks can be not only measured and understood, but augmented and strengthened through predictive strategies.
the trinity session
As previously discussed, the types of network analysis listed are most often applied to communication efforts within corporations and/or financially oriented endeavors. However, it is undeniable that the same type of measures can be and have been effectively applied to any network structure, in the interest of uncovering patterns of efficient and effective capital transfer (social, material etc.) and further, to the improvement of that flow.
The trinity session is an artist collective based in Johannesburg, South Africa, involved in both benevolent and commercial projects. Their interest is in promoting South African art and cultural, both within South Africa and internationally.
The trinity session, as the name implies, is a classic triadic network structure; three individual artists who each bring their own set of contacts and connections together. In the relatively tight network structure (small community) of South African artists, each maintains an extensive list of contacts and independent projects, in addition to a wide range of collaborative projects that makes use of both individual and mutual connections.
The considerable success of the trinity session in their relatively short history is arguably a result of the utilization of the network that they have cultivated.
In an effort to combine the structures of network analysis and complex adaptive system theory, I propose to spend five weeks in Johannesburg and Cape Town, applying observational and quantitative measures to the function of the trinity session within a project environment. I will participate in several ongoing project executions, as well as interview and interact with extended members of the trinity session network, both socially and professionally. The product of this study will be an emergent visualization and theoretical assessment of the functions of individual actors (nodes), the relation between each pair (dyadic), interaction between all three members (triadic) and an overview of the function of the members within their cultural sub group (clique subsystem).
The interest in focusing on this group is to uncover implicit and explicit strategies, both successful and unsuccessful, in the pursuit of cultural and social development through practices of social networking.
Methodology
As a standard approach to communication network assessment, the structure of the project assessment will take the form of the MTML approach, as discussed by Conge and Contractor (Theories of Communication Networks, 2003).
The Multitheoretical Multilevel Model, or MTML, provides a powerful application of several elements of social network analysis. It provides both a conceptual and practical framework with which to assess the form and function of network attributes and features.
Combining traditional graph theory in the tradition of Moreno and Jennings, who introduced the sociogram or dyadic network analysis, and p* statistical network techniques, the MTML method strives to create both a visually substantive and statistically sound description of network structures.
The following is a partial list of the considered attributes in the MTML framework.
Linkage
Indirect Links
Frequency
Stability
Multiplexity
Strength
Direction
Symmetry (reciprocity)
Individual Actors
Degree
Indegree
Outdegree
Range (diversity)
Closeness
Betweeness
Centrality
Prestige
Roles
Star
Liason
Bridge
Gatekeeper
Isolate
Network
Size
Inclusiveness
Component
Connectivity (reachability)
Connectedness
Density
Centralization
Symmetry
Transitivity
Bibliography
Axelrod, Robert. (1997). The Complexity of Cooperation. New Jersey: Princeton University Press.
Barabási, Albert-László (2002). Linked. Cambridge: Perseus Books.
Dawkins, Richard (1976). The Selfish Gene. New York: Oxford University Press.
Degenne, A & Forsé, M. (1994; 1999). Introducing Social networks. London: Sage Publications.
Holland, John. (1995). Hidden Order: How Adaptation Builds Complexity. Cambridge: Perseus Books.
Monge, P.R. & Contractor, N.S. (2003). Theories of Communications Networks. New York: Oxford University Press.
Putnam, R.D. (2000). Bowling Alone. New York: Simon and Schuster.
Scott, John. (2000). Social Network Analysis: A Handbook (second edition). London: Sage Publications.
Taylor, Mark C. (2001). The Moment of Complexity. Chicago: University of Chicago Press.
Axelrod, Robert. (1997). The Complexity of Cooperation. New Jersey: Princeton University Press.
Barabási, Albert-László (2002). Linked. Cambridge: Perseus Books.
Dawkins, Richard (1976). The Selfish Gene. New York: Oxford University Press.
Degenne, A & Forsé, M. (1994; 1999). Introducing Social networks. London: Sage Publications.
Holland, John. (1995). Hidden Order: How Adaptation Builds Complexity. Cambridge: Perseus Books.
Monge, P.R. & Contractor, N.S. (2003). Theories of Communications Networks. New York: Oxford University Press.
Putnam, R.D. (2000). Bowling Alone. New York: Simon and Schuster.
Scott, John. (2000). Social Network Analysis: A Handbook (second edition). London: Sage Publications.
Taylor, Mark C. (2001). The Moment of Complexity. Chicago: University of Chicago Press.