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First presented to The Developing Group on 3 June 2006
(an earlier version, Thinking Networks I, was presented on on 5 June 2004)

Thinking Networks II

James Lawley


Our aim is:
"To get you to think networks.
It is about how networks emerge, what they look like, and how they evolve. ...
Networks are present everywhere. All we need is an eye for them."
Albert-László Barabasi Linked, p.7



Contents

1. Introduction

2. Components of Network Theory

3. Key Features of Networks

a. Pattern of Organisation

b. Interconnectivity

c. Irreversibility

d. Nonlinearity

e. Unpredictability

f. Dynamic equilibrium

g. The rich grow extraordinarily richer

h. The butterfly effect

i. The inverse butterfly effect

j. No one is in control

4. Further Reading

Note: There are three types of description in this paper:

i. Paragraphs like this are my summary of some of the key concepts in network theory. Words in bold are the key concepts and are followed by a popular definition. Words in curly brackets are alternate descriptions/metaphors, e.g. links {ties, bonds, connections}.

ii. Quotations are usually this size and indented. Italics are in the original, bold is my addition.

iii. [JL: Words in square brackets are my attempt to use network theory to explain and guide the personal change process.]

1. Introduction

I'll start with a tribute to Fritjof Capra who made an early and significant contribution to bringing the importance of networks to my attention when he asked:

"Is there a common pattern of organization that can be identified in all living systems? ... this is indeed the case. Its most important property is that it is a network pattern. Whenever we encounter living systems ... organisms, parts of organisms, or communities of organisms -- we can observe that their components are arranged in network fashion. Whenever we look at life, we look at networks." The Web of Life, p. 81-82

The kinds of networks we shall be considering are complex adaptive or complex dynamic networks. Complex, not necessarily because of the number of links and nodes, but because of the intricacies of the interconnections. The collective behaviour of a complex adaptive network is not just more than the sum of the parts, it's something entirely different. Adaptive, because these networks respond to external and internal events and therefore they are always changing — they are dynamic — both at any moment and over periods of time. Although adaptation is a signature of organic networks, mechanical and social networks adapt too. The internet for instance automatically responds to the addition or removal of a link or node by re-routing messages via new nodes and links or around failures; and the users of the World Wide Web (www) spread the news of the arrival of a better search engine called Google like wildfire. In other words, complex adaptive networks are intelligent.


However, none of this would be very interesting if it wasn't for the fact that inspite of their complexity, inspite of the adaptive and dynamic nature of these networks, recent research has shown them to have remarkably consistent patterns of organisation.

To understand the science of networks you have to think differently about the world — and that, in my opinion, is the main reason for a facilitator to study network theory. Time and again netwrok researchers emphasise that in order to think in terms of networks, a new way of thinking is required:

"We're accustomed to thinking in terms of centralized control, clear chains of command, the straightforward logic of cause and effect. But in highly interconnected systems, where every player ultimately affects every other, our standard ways of thinking fall apart." Sync, p. 34-35

"The resulting small worlds are rather different from the Euclidean world to which we are accustomed. ... Navigating this non-Euclidean world repeatedly tricks our intuition and reminds us that there is a new geometry out there that we need to master in order to make sense of the complex world around us." Linked, p. 40

"When it comes to large-scale coordinated social action, hindsight is not 20-20 -- in fact it can be actively misleading. ... The small-world phenomenon is so counterintuitive -- it is a global phenomenon, yet individuals are capable only of local measurement." Six Degrees, p. 53 & 83

"What makes this paradoxical is that you might think that strong social links would be the crucial ones holding a network together. But they aren't; in fact they are hardly important at all. ... We are continually surprised [because] the long-distance social shortcuts that make the world small are mostly invisible in our ordinary social lives. We can only see as far as those to whom we are directly linked." Nexus, p. 41 & 55

Before we delve into the features of complex adaptive networks let's take a brief look at the fundamental concepts of network theory.

James Lawley

James LawleyJames Lawley is a UKCP registered psychotherapist, coach in business, and certified NLP trainer, and professional modeller. He is a co-developer of Symbolic Modelling and co-author (with Penny Tompkins) of Metaphors in Mind: Transformation through Symbolic Modelling. For a more detailed  biography see about us and his blog.

 
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