I am happy to announce a new major release of Social Network Visualizer (SocNetV), the Social Network Analysis software. SocNetV v2.0 comes with a major code overhaul for stability and performance boost, improved GUI with a new panels layout, and nice new features for easier social network analysis, such as separate modes for graphs and digraphs, permanent settings/preferences functionality, edge labeling, recent files, keyboard shortcuts, etc. Also there are improvements in Force-Directed layouts, i.e. Fructherman-Reingold. The new version supports Windows, Linux and Mac OS X. Binary installers and source code packages are available from the project’s Download page. See below a walk-through of the new features.
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By default the Qt5 libraries distributed from qt.io are dynamically linked. This means that every Qt app dynamically references and uses the Qt prebuild libraries (.dll or .so) it depends on. So in order to deploy your Qt app to your users, you need to find the relevant Qt libraries and distribute them as well (or make sure all other PCs have exactly the same Qt environment as your development PC), which is a pain. That is why it’s easier to build a static version of your application – one single standalone executable with all libraries included inside. But to build a standalone executable of an app you need a static version of Qt libraries. If you target Windows 7/8, you might want to use the Powershell described in qt.io documentation to build a static Qt for Windows, but you can also compile a static Qt5 from scratch on your own. And no, it’s not that difficult…
Another release has just emerged from the depths of the Social Network Visualizer project! The new version 1.9 fixes important bugs and brings a vastly improved matrix inverse algorithm, thanks to the newly implemented LU decomposition. Of course, the new algorithm speeds up all other routines which depend on the inverse of a matrix, such as the Information Centrality algorithm.
Also, SocNetV v1.9 brings a revamped -and corrected- PageRank Prestige routine. Up to v1.8, the PageRank algorithm was using the original Page&Brin formula which lead to somewhat different results compared to other SNA applications. From this version, SocNetV uses the correct formula and computes comparable results (yes, we tested :)).
Source code, Windows zipped executables, Mac OS image and binary packages for major Linux distributions are as always available from the project’s Downloads page. Have fun with the new release!
Also, I am happy to report that the Qt project has added SocNetV to its ‘showroom’ page, along with many other nice Qt applications. There is also a showroom page dedicated to SocNetV with nice screenshots and a brief description of the application. Kudos to Kojo Tero, of Qt Company, for this!
A new SocNetV release hit the road today. Version 1.7 solves a number of bugs and brings lots of interesting and useful new features to our users. Binaries for Windows, Mac and Linux are already available in the project’s Downloads page. Here’s what’s new…
The Social Network Visualizer project has just released its latest version 1.6. This new version brings back the web crawler feature, which has been disabled in the 1.x series so far, but in a much more improved form.
To start the web crawler, go to menu Network > Web Crawler or press Shift+C…
One of the daily routines administrators do is to monitor their web server logs for various interesting things: response codes (i.e. 500), attempts to access restricted pages, user-agents, ips, popular pages, even image hotlinking from other sites. In Linux servers, this can be easily done through shell one-liners involving various tools (tail, awk, sort, cut etc). Here is a bash script I use which automates apache monitoring for a given website.
When I started developing SocNetV back in 2005 the term “social network” had a simple sociological meaning; any group of somehow “connected” actors, which might interest a sociologist to study and analyse in terms of their social properties and patterns (centralities, triads, etc). The actors can be of any type (humans, animals, organisations, companies etc) and so the cause of them being connected: working in the same place, belong to the same hive/group, mentioning each other, having commercial relations etc. Thus the main reason behind developing SocNetV was to create a simple “point and click” application that would enable the researcher to load his real-life gathered data and visualize/analyze the network properties. Or, in case the network was small enough, perhaps recreate it with some clicks on a canvas before analysing it. Back then it had never occurred to me that the same “social network” would be used now-days to describe online communities of million of users. As a matter of fact, I always thought that this strand of sociology is more meaningful in analysing relatively small groups rather than thousands of interconnected actors. Nevertheless, the term is used now this way too and this means that Social Network Analysis software such as SocNetV face a new problem: people not knowing anything about Social Network Analysis as a hybrid sociology-mathematics discipline think that all the software does is to “automatically” analyse any given online virtual community; who is connected to whom and how. Which is certainly not true.
