dimitris kalamaras

mathematics, social network analysis, free software…

Month: May 2015

SocNetV v1.7 brings Group Node Edit, new Properties dialog, file Previewer and more

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…

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SocNetV v1.6 released – a nice web crawler included!

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…

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An apache monitoring script

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.

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SocNetV and online social networks

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.

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