UNDERSTANDING CONTAGIOUS DIFFUSION USING NETWORK DIAGRAMS

As the social web moves beyond the hype stage, and the monetisation phase takes a grip, we all need to start understanding how contagious diffusion really works in different types of communities. We'll need to master how to construct network diagrams that show all the nodes in a network, and how the influence flows.

I'm starting to experiment with something called Gephi. It's an interactive visualization and exploration platform for all kinds of networks and complex systems, dynamic and hierarchical graphs. It's open source and therefore free. I'm trying to get data sources, and posted a question on Quora (if you can help).

Gephi demo at JavaOne from gephi on Vimeo.

I see this as a form of digital anthropology. Over the next few years, we will all use data and software like this to dive into the community and really understand what makes it tick. I currently use a series of qualitative techniques fortified with data coming from search analysis and online conversation analysis through Alterian SM2, but getting dynamic data-sets into something like Gephi is the next stage. I've posted on graph theory and network analysis before, and how we will need to master language like clustering coefficients, centrality, and betweeness, and other language that describes networks, but that future is now here.

Introducing Gephi 0.7 from gephi on Vimeo.