I’m excited to be off to the Digital Methods Winter School in Amsterdam tomorrow! The first day is a mini conference (and look at all the interesting stuff in the reader!) and then there’s a three day workshop where we actually do data sprints and hands on work with data capture and “abbreviated analysis”.
Richard Rogers and Sabine Niederer came up from Amsterdam to run a mini-workshop for us here in Bergen last June, which gave us an excellent sampling of how they work. Since then, we’ve been slowly been building up our skills and knowledge in data visualisation, social network analysis and similar, and we’ve been having a lot of fun. Last night, Scott put together a visualisation of all the works and authors in the ELMCIP Knowledge Base of Electronic Literature – here’s a screenshot, but click through to the interactive web version to really play with it.
Scott and I have written a paper – or really, a work-in-progress report – for the conference, Mining the Knowledge Base: Exploring Methodologies for Analysing the Field of Electronic Literature, where we discuss the different approaches we’ve been taking to visualising and analysing the data in the Knowledge Base. We’ve tried word clouds, social network analysis using Gephi, and want to try directly analysing web data associated with the information in the Knowledge Base (e.g. from author or journal or event websites, or from Twitter accounts and conversations or Facebook pages) in a more authentically digital methods style approach.
Much more to come – it’s a lot of fun seeing how we can visualise the data about the field of electronic literature that we’ve gathered over the last few years.
I’m also looking forwards to using these tools with students in DIKULT251, the upper-level undergraduate course I’m teaching this semester, which is focused on social media.
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Ted Ortiz
Especially when using social network analysis as a tool for facilitating change, different approaches of participatory network mapping have proven useful. Here participants / interviewers provide network data by actually mapping out the network (with pen and paper or digitally) during the data collection session. One benefit of this approach is that it allows researchers to collect qualitative data and ask clarifying questions while the network data is collected.