Peter Gloor has created a revised version of his book on collaboration and innovation. It is now titled, Net Creators: How to Build Lasting Value Through Social Webs of Innovation. It is available through this link. I think this book, and TeCFlow, the tool he describes, represents a breakthrough in ways to look at social interactions. Here is a long quote from the opening to Chapter 15 of the book which introduces the tool and the concept behind it.
“If you are a lover of classical music, imagine listening to a sonata from Beethoven. After the music has been introduced in the exposition, it will undergo a modulation and will arrive at the end of the exposition in a different key. As the melody further develops, you will more and more be able to unravel the tune and to analyze and understand the underlying patterns of the melody. The longer you listen to the tune, the better you will know what to expect next. The TeCFlow tool allows you to do the same for the evolution of interaction patterns in social networks. TeCFlow, a Temporal Communication Flow Visualizer, is currently being developed as part of a research project on CKNs at the MIT Center for Coordination Science and the Center for Digital Strategies at Dartmouth. Our goal is to build an environment for the visual identification and analysis of the dynamics of communication in social spaces. Similarly to an orchestra playing a musical melody, our tool plays back an interactive movie depicting the interaction between members of a team based on their e-mail traffic. By comparing dynamic interaction patterns with the performance of virtual teams, we can identify typical communication patterns of different types of virtual communities.”
Peter then provides many examples of how TeCFlow can be used to look at social interaction patterns. He characterizes the ideal patterns in three stages of innovation – the initial innovation group (COIN), the resultant learning network (CLN), and the broader community of interest (CIN). Then he offers insights on how these interactions can be improved to better achieve the communities’ intended objectives, whether they are a successful merger, an innovative new product, or a productive sales campaign. There is much rich material here and the temporal visualization of social patterns makes it all very clear.
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