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Editors’ Choice: Networks Analysis Round-up

Editors’ Note:  For those interested in networks and network visualization, a series of posts from Scott Weingart and Elijah Meeks that introduce, explain, and provide examples and instructions for the analysis of networks are linked below. *updated 1/4/12*

Scott Weingart, Networks Demystified 2: Degree, December 17, 2011

  • Today I’ll cover the deceptively simple concept of node degree. I say “deceptive” because, on the one hand, network degree can tell you quite a lot. On the other hand, degree can often lead one astray, especially as networks become larger and more complicated. A node’s degree is, simply, how many edges it is connected to. Generally, this also correlates to how many neighbors a node has, where a node’s neighborhood is those other nodes connected directly to it by an edge. In the network below, each node is labeled by its degree. Read Full Post Here.

Scott Weingart, Demystifying Networks, December 14, 2011

  • A bunch of my recent posts have mentioned networks. Elijah Meeks not-so-subtly hinted that it might be a good idea to discuss some of the basics of networks on this blog, and I’m happy to oblige. He already introduced network visualizations on his own blog, and did a fantastic job of it, so I’m going to try to stick to more of the conceptual issues here, gearing the discussion generally toward people with little-to-no background in networks or math, and specifically to digital humanists interested in applying network analysis to their own work. This will be part of an ongoing series, so if you have any requests, please feel free to mention them in the comments below (I’ve already been asked to discuss how social networks apply to fictional worlds, which is probably next on the list). Read Full Post Here.


Elijah Meeks, More Networks in the Humanities or Did books have DNA?, 12/6/11

  • I thought, though, that I might post the slides I used to describe networks in general and the examples using network analysis and representation based on the literature network that Matt has produced for his research. I’m never sure about who’s in a digital humanities audience and whether they need to have the most basic aspects of a network explained.  As I said during the presentation yesterday, I think there are three pillars to DH research: Text Analysis, Spatial Analysis and Network Analysis.  The network is not a social network or geographic network or logical network but rather a primitive object capable of and useful for the modeling and analysis of relationships between a wide variety of objects.  I continue to have a sneaking suspicion that Image Analysis is something else that sits with the aforementioned three, especially after witnessing the presentations at HASTAC. Read Full Post Here.


Scott Weingart, Contextualizing Networks with Maps, 11/22/11

  • Just as networks can be used to contextualize text (and vice-versa), the same can be said of networks and maps (or texts and maps for that matter, or all three, but I’ll leave those for later posts). Now, instead of starting with the maps we all know and love, we’ll start by jumping into the deep end by discussing maps as any sort of representative landscape in which a network can be situated. In fact, I’m going to start off by using the network as a map against which certain relational properties can be overlaid. That is, I’m starting by using a map to contextualize a network, rather than the more intuitive other way around. Read Full Post Here.


Scott Weingart, Topic Modeling and Network Analysis, 11/15/11

  • Since shortly after Blei’s first publication, researchers have been looking into the interplay between networks and topic models. This post will be about that interplay, looking at how they’ve been combined, what sorts of research those combinations can drive, and a few pitfalls to watch out for. I’ll bracket the big elephant in the room until a later discussion, whether these sorts of models capture the semantic meaning for which they’re often used. This post also attempts to introduce topic modeling to those not yet fully converted aware of its potential. Read Full Post Here.


Elijah Meeks, Visualization of Network Distance, 11/11/11

  • I’ve just finished my first Gephi plugin, which distorts a geographically laid out network to emphasize network distance. The NBM can be found here and the source code is on GitHub. The layout takes the XY coordinates of the node and maintains their angle from a defined central node but increases the distance to match network distance. This is better shown than written. It was created for Walter Scheidel, who wanted to see how the transportation network of Imperial Rome would look if subject to the same transformations he’d seen applied to the London Subway network. Read Full Post Here.

This content was selected for Digital Humanities Now by Editor-in-Chief based on nominations by Editors-at-Large: