Presumably, if the ideas are too different, there will only be incomprehension and misunderstanding. It is like two cultures coming together when people fight rather than trades. It is like listening to jazz for the first time; it sounds like a cacophony. So there has to be some common ground. But if the ideas are too similar there won't be sufficient mix. Thomas Kuhn's Structure of Scientific Revolutions might distinguish between the creeping progress phase when the ideas are very similar and the revolutionary phase.
Networking is a way of bringing people together. The power of Facebook shows how much people enjoy (social) networking. Other websites, such as LinkedIn, exist to encourage professional networking. The rise of the coffee house gave birth to Lloyds but it was probably also responsible for the rapid spread of ideas that became known as the Enlightenment and gave us the scientific, political and commercial concepts on which the modern world is based.
Reinelt (2010) suggests that "Networks scale when people in networks reach across divides (e.g., race, sector, issue, interest) and build bridges that enable them to exchange ideas, share resources, and collectively self-organize to influence fields and policies. Boundary-spanning begins with conversations to find connections. These connections form clusters that lead to stronger webs of relationships and eventually robustly link networks to other networks -- a fundamental prerequisite for scaling. "
Ricchiuto 2010 offers the 4 Laws of social networks:
- Serendipity "happens at the intersection of (network) consciousness and being transparent about one's gifts and passions"
- "Innovation happens at the intersection of learning and cultivating diverse connections"
- "Influence happens at the intersection of credibility and location in the network"
- Networks grow when there are many introductions and the people who are introduced are generous, giving without expecting reciprocity.
This tells us little other than that Ricchiuto believes that networks work if the people in them are transparent, generous and credible; if they cultivate diverse connections and make intorductions; and if they are ready to learn.
Malcolm Gladwell (2000; p259) lists the factors that cause what he calls social epidemics: "We are powerfully influenced by our surroundings, our immediate context, and the personalities of those around us .... Merely by manipulating the size of a group, we can dramatically improve its reception to new ideas. By tinkering with the presentation of information, we can significantly improve its stickiness. Simply by finding and reaching those few special people [people who cultivate friendships; people who have acknowledged in-depth expertise such that other people will take their advice, and people who know how to persuade] .... we can shape the course of social epidemics."
For Gladwell, therefore, networks need to be the right size, and in the right context, and the people in them need to be well-connected, persuasive and acknowledged experts. It also helps is the information is 'sticky'.
One of the things we know about networks is that they generate feedback loops. In another posting, Krebs (2010b) points out that positive feedback created the bubble in the sub-prime mortgage market that led to collapse. This is easy to spot in hindsight; why couldn't the players within the feedback loops spot the dangers earlier? His suggestion is that each part of the feedback loop was below the 'network horizon' of the other part. "In networks, any path longer than 2 steps is usually considered "over the horizon" -- one cannot see, nor influence, over the horizon. In networks, distance leads to distortion, delay, and increased risk."
He has already explained this idea in an earlier post (2010a)."After one step the message begins to grow fuzzy, after two it is becoming very noisy, and after three it is basically useless -- background hum. We might be all separated by six degrees but it is the first two steps that really matter." He also points out that nodes in the network differ in how quickly they pass on information. So if you want to get your message out there DON'T rely on a single connector or maven; get your message to several nodes in different parts of the network or as Krebs puts it: build in redundancy.
This delay idea leads me to think of the beer game described by Senge (2006). In this modelling of inventory stocks it is an inbuilt delay in receiving information which leads to disastrous stock fluctuations.
If you consider twitter as a network there are perhaps three sorts of tweeter:
- Those who follow many and are followed by a few: these tweeters learn a lot and develop a great deal of expertise: in Gladwell's terms these are the mavens who collect knowledge and therefore develop a reputation for expertise: their followers listen to them;
- Those who follow a few but are followed by many: these are the salesmen, the persuaders
- Those who follow many and are followed by many: these are the connectors
Might also be worth reading this post (14th December 2009)
References
Gladwell M 2000 The Tipping Point Abacus London
Krebs V 2010a Spread of Influence in a Network (27th February 2010) blog posting on TNT - The Network Thinkers http://www.thenetworkthinkers.com/ accessed 7th November 2010
Krebs V 2010b In the Dance of Debt - Who is Leading? (10th October 2010) blog posting on TNT - The Network Thinkers http://www.thenetworkthinkers.com/ accessed 7th November 2010
Krebs V 2010c Networks on the radio (30th October 2010) blog posting on TNT - The Network Thinkers http://www.thenetworkthinkers.com/ accessed 7th November 2010
Ricchiuto J 2010 The 4 Laws of Networks (17th Feb 2010) on Network Weaving available at http://networkweaver.blogspot.com/2010/02/4-laws-of-networks.html accessed 7th November 2010.
Reinelt 2010 Comment (22nd Feb 2010) on blog Network Weaving available at http://networkweaver.blogspot.com/2010/02/4-laws-of-networks.html accessed 7th November 2010.
Senge P 2006 The Fifth Discipline. The art and practice of the learning organisation. Random House London
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