Mastering Gephi Book Update

Lest anyone think of me as a full-time author, rest assured that the likes of J.K. Rowling are not trembling in fear. Even if I had the ability to conjure up creative plots, I type too damn slow to make it as a full-time literary lion. Fortunately, I don’t have to depend on my keyboarding skill (or lack of) as a full-time pursuit. Which brings me around to my topic – the current book I’m authoring on Gephi.

For those not exposed to networks and network analysis, Gephi is a French-based open source project that makes it possible for all sorts of users (including moi) to create interesting graphs from connected datasets. By connected I am referring to data where the individual nodes are connected in some way, shape, or form. This could be anything from movie actor databases, Facebook friend networks, baseball player connections, and so on. Anyone with a spreadsheet full of data and a bit of effort and persistence can use Gephi to create cool looking graphs that also tell a story of some sort.

My job in writing the book is to help people make sense of all the features and capabilities within Gephi, some of which are a bit complex to master. In the process, I get to learn more about the theory behind network analysis, and with it terms such as contagion, diffusion, clustering, and homophily. It’s really fascinating if you’re into understanding how people and institutions interact, contagion processes function, or how product adoption can be affected by the structure of a network. My higher math skills are not good enough to be at an academic level with this stuff, so I have to compensate with some logic and visual acuity.

Anyhow, here’s some of the stuff that Gephi can create:

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I’m hoping that one of these images will serve as the book cover come publishing time, which should be sometime this fall. In the meantime, I have six more chapters to write (of 10 total), and will have the added joy of working through chapter edits where others catch the mistakes I’ve made.

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kc2519

kc2519

Ken Cherven is the Founder and Curator of the Visual-Baseball.com website. He loves to merge baseball data with all sorts of visualization methods - charts, network graphs, maps, etc. to provide greater insight into underlying data patterns. Ken also authors books about baseball and visualization, and loves to listen to jazz while drinking some wine, craft beer, or bourbon.