Layered, Emergent and Adaptive Communication Network Systems

Lorraine Kisselburgh

This week, Noshir Contractor introduces a rich array of information in discussing communication networks, new grid infrastructures, and social networking tools that can be leveraged to strengthen our communities – whether social, work, virtual, or even “exotic”. What follows are some observations about social networking tools, visualization tools, and communication network theories.

Flaws in social networking – privileging the topical and the cognitive
Current social networking tools, like speed dating, appear to privilege the topical creation of a link – i.e. who we know – while ignoring the meaning of such links and the strengthening of links through social interaction, both of which are essential to forming strong ties in a community. Thus, we typically illustrate the density of network structures, but not their depth nor their relationship strength. This also means that the dynamic process of maintenance, dissipation, and recreation of these links may not be adequately represented.

Similarly, the communication network systems tend to privilege the cognitive, focusing more on information exchange and sharing, and less on social/emotional factors underlying communication and organizing. We know that communities and networks are influenced by factors other than knowing someone. Is it possible to weight links (relationships) so that we assign attributes such as trust, reliability, and other influence factors? Identification of these attributes enrichen our information about (and subsequent use of) a link, node, or network. [1]

In this, I’m reminded of something from John Seely Brown and Paul Duguid’s book “The Social Life of Information” (2000): “We need …to look beyond our obsession with information and individuals to include the critical social networks of which these are always a part.”

In other words, communication networks reflect the intersection of social and information. Further, we might even say that our social networks and information networks are differently represented: they may overlap, but be entirely different network representations.

Dr. Contractor addresses this in his aphorisms of communication networks, stating that cognitive social networks can be characterized as “not what you know, [but] what who you know knows.”

New Visualization Tools
In addition, we need to recognize the many layers of networks that individuals participate in – layers that overlap and intersect. For example, my social and information networks for Communication (my work/study organization) may be quite different than my social and information networks for IT (my previous work/study organization), my residential neighborhood, or my family. I continue to participate in each of these networks, of course with varying degrees of involvement and regularity.

Current visualization tools are two-dimensional, and fail to represent these layers and overlaps. The development of three-dimensional visualization tools, similar to GIS mapping systems, could provide layered mappings of networks and allow us to choose to reveal those networks that are relevant and pertinent to what we’re doing or seeking, and overlay these as necessary.

For example, this could also be useful for communities of scholars within a University organization, particularly with the growth of interdisciplinary collaboration. There might be a network of Life Sciences scholars, a network of Psychology scholars, and a network of Engineering scholars. Through their collaborative activity, individuals might transcend their “home” network to connect with and become a part of a different network, while still maintaining membership at “home”. A crude rendering of this (without accessing 3-D drawing tools) would be (click here).

In this rendering, the bottom layer could represent the social layer and the next the information layer. Alternatively, the bottom layer could represent the Life Sciences network and the second layer the Engineering network. Depending upon my needs, I may choose only to reveal and examine a single layer; in other settings I may need to access information about both at the same time, and see them overlaid to reveal overlaps and interactivity (internetwork connections).

In another perspective, in recognizing these multiple dimensions – or layers – of networks, we can begin to approach communication from socio-cultural, organization, and individual levels.

Moving beyond description to simulation and prediction
In addition, while current social network analysis tools have been useful in helping us to understand human behavior, I think the real value (in enabling communities, at least) comes from being able to do predictive and simulation activities that would contribute to more effective decisions people make about their management of communication, relationships, and organizing.

In fact, it appears that Dr. Contractor does indeed have such a project under development called “Blanche”, using computational modeling tools to simulate network activity and development.

Further Theoretical Development
What about the state of current theoretical development in communication networks? Current theories still privilege the state of information gathering (info resources) and don’t well incorporate other resources we seek as humans (e.g., gratification, self-esteem, security, or just the yearning for human connection) when making communication choices. While organizational communication is certainly more focused on information flows, we are still social beings at heart.

Furthermore, many of the theories of communication networks are based upon a presumption of rational, strategic decisions that are made about our communication (Monge and Contractor, 2003). But research shows that a lot of human behavior is neither rational nor strategic – and includes impulsive, unplanned, chance encounters that (may) lead to productive connections and relationships.

In other words, communication (and communication networks) sometimes ‘evolves’ or ‘emerges’ from the daily living of life, in ways that are not well covered by existing communication network theories that are based upon systems theory perspectives of organizations and organizing.

Instead, as Dr. Contractor has introduced, communication systems are very dynamic and sometimes unpredictable, and it is important that our models account for this. How can new communication theories account for human variation, irrationalities, constant states of flux (i.e., the elements of chance and chaos), and include an acknowledgement of the emergent properties of social and information networks? Is it possible to build social network theories (and tools) that expect and predict human variation as part of the system?

In quick closing, we need new theories and tools that explain and support layered, emergent and adaptive communication network systems.

[1] A caveat: my understanding of social networking analysis is still elementary.


Brown, J.S. and Duguid, P. (2000). The social life of information. Boston, MA: Harvard Business School Press.

Contractor N., Zink, D., & Chan, M. (1998). IKNOW: A tool to assist and study the creation, maintenance, and dissolution of knowledge networks. In Toru Ishida (Ed.), Community Computing and Support Systems, Lecture Notes in Computer Science 1519 (pp. 201-217). Berlin: Springer-Verlag.

Contractor, N. (2002). Introduction: New Media and Organizing” In Leah Lievrouw & Sonia Livingstone (Eds), Handbook of New Media: Social Shaping and Consequences of ICTs (pp. 201-205). London: Sage.

Contractor, N. S., & Monge, P. R. (2002). Managing knowledge networks. Management Communication Quarterly, 16, 249-258.

Contractor, N. (2003). Peer to peer. In S. Jones (Ed.), Encyclopedia of New Media (pp. 367-369). Thousand Oaks, CA: Sage.

Monge, P. R., & Contractor, N. (2003). Multitheoretical, Multilevel Models of Communication and Other Organizational Networks . In Theories of Communication Networks (pp. 293-327). New York: Oxford University Press.

Hollingshead, A. B., & Contractor, N. S. (2006). New media and small group organizing. In S. Livingstone & L. Lievrouw (Eds.), Handbook of New Media: Student Edition. (pp. 114-133). London: Sage.

One thought on “Layered, Emergent and Adaptive Communication Network Systems

  • May 3, 2006 at 1:22 pm

    Two thumbs way up for the comments about the need to measure depth and quality of ties. I completely subscribe to these ideas. But, you might be surprised, some of this work is being already done. Even Nosh’ work is focused on multidimensionality of knowledge.


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