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Adobe pdf file An Introduction to Network Analysis as a Research Technique - 2012 Version . From time to time I run a half-day seminar called “Introducing Network Analysis as a Research Technique”. The next seminar will occur on the afternoon of Tuesday the 31st of January at the University of Canberra.

The seminar is aimed at new researchers. It has been substantially upgraded and revised, and includes an example that illustrates pitfalls for researchers and analysts. It is organised into four sessions as follows:

I've spent the last few days as an invited speaker at the Australian Institute of Professional Intelligence Officers annual conference. My topic was "Using Social Network Analysis as an Intelligence Technique ", with a sub-title of "Sometimes a Picture is Only Worth a Few Words!" One of my concerns is that people have become enamoured with visualisation at the expense of analysis - they are doing social network visualisation, not social network analysis. Worse they are applying algorithms, such as closeness centrality without actually understanding what the algorithms produce, and what their limitations are. So building on these concerns I borrowed a concept from Dr Marc Smith, which he calls Network Nirvana, as the means to illustrate my concerns. Network Nirvana is achieved when every node is visible, every link is visible and direction can be discerned, degrees can be counted, and clusters are clearly visible.

The presentation began with a quick network lesson, where I discussed bounded and unbounded networks, and directed and undirected networks. Understanding what type of network you are working with is important because it changes the equations used to calculate various measures, and indeed whether certain measures can be used with confidence. For example, closeness centrality can only be used with confidence in a bounded network. (Some authors say it should only be used in a bounded network.) I then used a case study on Iranian Nuclear Physicists to illustrate the dangers of blindly doing social network visualisation and applying common algorithms that are readily available in the software tools, instead of doing a structured social network analysis.  In particular I showed how social network visualisation that does not achieve Network Nirvana can lead to false conclusions.

Last week I looked at the packages and licencing arrangements in NetMiner 4. My conclusion was that some elements, like the Explore package and query composer and graph editor, should really be part of the standard Basic Package. I also challenged the Royalty licencing model which does not work for a small business, and received a couple of supporting comments. In this post I propose to look at the help system, with subsequent posts looking at the analytical, visualisation, statistical, and scripting capabilities.

I’ve been using NetMiner since 2005, beginning with version 2.3. I keep renewing or upgrading my licence because in my opinion the visualisation capabilities are unmatched by any other tool on the market, at least the tools I can afford. Couple this will an outstanding help system and an output that includes the analytics on the same screen, or a window, and the tool is unrivalled.  Depending on which packages you buy you have 28 or 36 analysis options, ranging from centrality, block-modelling and brokerage, to homophily and page rank, and measures for two-mode networks. However for the beginner, and even the intermediate, user these can be a bit daunting, and this is where the help system comes into play.

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E-mail: graham@durantlaw.info

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