Making Personal Network Analysis More Accessible
Bernie Hogan, Research Director, NetLab, UofT
In this talk, Bernie is talking about tools to make use of personal network analysis and make it accessible to the average user. In yesterday’s presentation, Bernie talked about the Connected Lives project which studies individuals from East York. It is difficult to analyze data that comes about from name generators. So the idea is to create a software to help to analyze the data that come out from name generators. Bernie and his colleagues at NetLab created visualizations of network data using participant-aided sociogram.
He is talking about how there is a problem with existing applications. They are designed for a single network (UCINET, NetDraw, Pajek), they have no GUI and steep learning curve (R, JUNG). So what they have done is modify existing applications, for example, GUESS (from Eytan Adar) + GraphModifier. Another problem is that the applications have virtually no interactive analysis. Batch processing of data has high fixed cost (have to know loops in R). So, the applications currently push in data, and then answers come out. What we want is data that goes in, answers come out and become source of new data. To address these issues, they created Egotistics software which is available on Sourceforge. In Egotistics, users can program, and batch process cohesive subgroups like k-plexes (I could have used that for my analysis!). One of the things to improve and encourage others to use Egotistics is to provide a web API to enable people to do analysis (not yet but should do).
I believe this talk really addresses how we need tools to discover communities and our social networks, so I'm going to look into these tools in a little more detail.
On Technorati: Social Networking Symposium, Egotistics
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