Emergent Behavior of Links and Clicks

One of the most interesting chapters in Mark Bernstein’s The Tinderbox Way is on links- both in Tinderbox and on the Internet. Mark provides a personal and historical overview of the approaches and attitudes toward linking beginning with the early days of hypertext and leading up to our current environment.

Linking evolved, guided by the users of the net in a way suitable for navigation within and between sites for readers. It’s  now adapted and grown to enable search advertising and the social networking systems.

What’s interesting to me is how difficult it is to show the utility of linking in a Tinderbox document. One ends up pretty quickly with a spaghetti plot of links between boxes. Mark provides some illustrations that look interesting but don’t seem to mean much at all as a map. There’s actually a site that collects these pretty network pictures: Visual Complexity.

As I read Mark’s discussion, I was struck by the similarity between these links and the interconnections of metabolic pathways within a cell or the interconnections between neurons. Mapped, we see spaghetti. But there is an emergent behavior from the network that only arises from the functioning of those interactions. On the web perhaps these are communities of shared interest.

We need a large amount of computational power to visualize the emergent network. Its easier if its geographical:

Via GigaOm:

If there’s one thing you get when you have close to 600 million users the way Facebook does, it’s a lot of data about how they are all connected — and when you plot those inter-relationships based on location, as one of the company’s engineers found, you get a world map made up of social connections.

We’re used to seeing maps as geographical metaphor. Maps of meaning are not well developed as mental models. I submit that Google’s algorithms for advertising and ranking are providing semantic functions that are such maps. The actual movement of people through the network as measured by following user clicks across sites is another even more important map. The data is massive and difficult to display simply, but the emergent behavior can be detected and used.

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