New Projects - Fresh from the Labs
According to SocNetV's Web site:
Social Networks Visualizer (SocNetV) is a flexible and user-friendly tool for the analysis and visualization of Social Networks. It lets you construct networks (mathematical graphs) with a few clicks on a virtual canvas or load networks of various formats (GraphViz, GraphML, Adjacency, Pajek, UCINET, etc.) and modify them to suit your needs.
The application can compute basic network properties, such as density, diameter and distances (shortest path lengths), as well as more advanced structural statistics, such as node and network centralities (i.e., closeness, betweenness, graph), clustering coefficient, etc.
I tried reading that a few times and my brain exploded, so I thought I'd give it a look and find out just what it was all about and explain it in human language. What I discovered was a deceptively simple yet sophisticated program that organizes collected data in very cool ways. Now, I must state from the outset that it has nothing to do with social networking in the guise of MySpace, Facebook and so on (although you could use it for plotting those things out if you really wanted to). SocNetV is a means of plotting data in new and original ways.
When you make your first few clicks, it appears to be just another basic plotting program, where you can make a flowchart or some other kind of information “tree”. Not so. The advanced mathematical features turn grid points into a fluid, almost organic organism that can change and adapt in real time and reveal all sorts of patterns and flow in what appears at first to be stagnant information.
If you head to the Web site's download section, SocNetV is available in packages for just about any distro you can shake a stick at, as well as a Windows binary, the usual source and even a Klik package (I haven't seen one of those for a while). I went with the Ubuntu package, but if your distro isn't on the list, or if you would prefer the source for whatever reason, you can do that too. If you are compiling from source, you need to grab the Qt4 development files, along with the QtWebKit development files. When you're ready, grab the source, extract it and open a terminal in the folder. From here, it's a case of doing the usual:
$ ./configure $ make $ sudo make install
Once the installation has finished, you can run the program by entering:
If you're lucky, it'll also be in your system's menu; mine was under Education→Mathematics→Social Networks Analysis and Visualisation.
Once inside, the first thing you'll see is a large blank white space, which is where your networks will be drawn. On the left are controls to Add or Remove a Node and to Add or Remove a Link. These are the most important controls, and you'll use them a lot. Now, let's create our first node.
Click Add Node, and a small yellow circle appears in the blank space on the right. This first node automatically becomes the first point of reference for all the other nodes, so it's best to make this node the most important—the nucleus, the genesis from which all the other nodes spring. With the node made, it's best to give this first node a label that sticks with the idea of it being a reference point.
Say you were mapping out your MySpace friends (goodness knows why, but let's run with it). You might want to name the first node something like “My Home Page”. Or, let's say you were a Dr Who fan mapping out the Dr Who universe; you might want to call the first node “The Doctor”, and so on. You can do this by right-clicking on the node, and choosing Options→Change Label.
Now, to add your surrounding nodes, click Add Node again, and a new node with the number 2 appears on the screen. To link this to node number 1, click Add Link. A series of prompts now appears in regard to the rest of the field of nodes, which is just the two for now. First up is the target node—1, by default. Next is the strength of the link, which, by default, will be 1.0. This value is very important, as it defines how valuable/important/relevant the link is to another node. You can use any number between –20 to 20, with positive numbers drawing a solid line between nodes and negative numbers drawing dotted lines. The higher the number, the thicker the line.
You've now connected your first two nodes, and from here I suggest adding some more to get the idea. If you right-click on a node, you'll notice the Options menu has a number of things to play with in terms of customizing each node, such as turning it into a square, changing the color and so on. Doing so helps differentiate one kind of node from another, helping to define what information it is representing visually. For instance, in my diagram of Metallica's history and affiliations (a band with a loaded history and a great deal of influence—a perfect testing ground for this kind of thing), band members are represented by a green circle, and bands/collaborators are represented by yellow circles.
You also can change the color of each line linking a node, adding more differentiation to a sea of probably messy information. For actual band members, I've gone with a strong gray line, with a dotted line for ex-members, and red line for the late Cliff Burton (RIP). Actual bands and important projects are signified by blue lines, and casual projects and one-offs are represented by pink lines. Don't forget that you also can move around nodes by left-clicking and dragging if things get messy and you need to do some rearranging.
Once you've made yourself a full grid of information, you can apply a bunch of crazy mathematics that can morph your information in real time, showing you new patterns in the information that you probably never thought of before. Check out the Layout menu and experiment with all the options for a real demo, which showcases what this program is really all about.
Although this project still has a few kinks and interface problems, anyone interested in the flow of information and discovering patterns in any area of life definitely should check out this project. In terms of industry, social analysts looking for new patterns in society, wealth and so on would find this of particular use. I'd also like to try using it in Analytical Psychology, mapping out various constellations of ideas in someone's psyche. There are endless uses for a tool like this that are limited only by your imagination—fascinating stuff.
John Knight is the New Projects columnist for Linux Journal.
Practical Task Scheduling Deployment
July 20, 2016 12:00 pm CDT
One of the best things about the UNIX environment (aside from being stable and efficient) is the vast array of software tools available to help you do your job. Traditionally, a UNIX tool does only one thing, but does that one thing very well. For example, grep is very easy to use and can search vast amounts of data quickly. The find tool can find a particular file or files based on all kinds of criteria. It's pretty easy to string these tools together to build even more powerful tools, such as a tool that finds all of the .log files in the /home directory and searches each one for a particular entry. This erector-set mentality allows UNIX system administrators to seem to always have the right tool for the job.
Cron traditionally has been considered another such a tool for job scheduling, but is it enough? This webinar considers that very question. The first part builds on a previous Geek Guide, Beyond Cron, and briefly describes how to know when it might be time to consider upgrading your job scheduling infrastructure. The second part presents an actual planning and implementation framework.
Join Linux Journal's Mike Diehl and Pat Cameron of Help Systems.
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