The methodology workshops have definitely helped a great deal in understanding what we can do with the student publications. Though we do get hints and pieces of the collection from writing up abstracts, the workshops help us engage with it much differently and more thoughtfully. The deliverables for the most part have been crucial in guiding us through the tools. We’ve had enough practice by now to come up with a ‘system’. Mostly brainstorm on a google doc, vote, then proceed with identifying sources, digging into archives, regrouping and putting together our findings.
The digital exhibit and mapping workshops and deliverables were pretty straightforward. One of the problems we encountered working with both Omeka and Timemapper was having a standardized format with which to enter information so that the tools can yield a consistent pattern and results. But we figured it out and resolved it; though some brushing up on metadata fields is still much needed.
My relationship with text analysis is superficial and complicated. While initially drawn in by the visualization tools in Voyant such as cirrus and links, Ilater
realized felt like there was nothing deeper beyond what it offered at a surface level. Perhaps there’s more to learn, but so far, the text analysis tool doesn’t seem strong enough to stand on its own as the main tool in a digital project, its more supplementary, rudimentary actually. I have to admit we struggled a bit coming up with abstracts for the text analysis deliverables, even having to move outside for inspiration.
However not all was lost. Topic modeling brought much more clarity to text analysis. I personally find it to be the most mind-blowing tool I have learnt about so far. First of all, MALLET a leading precedent for other forms of topic modeling software was borne in the pioneer valley, at Umass. On top of that, based on the project examples we looked at such as signs@40 and mining the dispatch , the uses are very versatile. Overall I would say one common thing about the workshops is that they reveal the research question doesn’t have to come first, it can come last. On top of that, the more I tools I learn about the more I notice that the research questions become open ended. We’ve shifted from asking what to why which opens up the possibilities for interesting research even wider.
I quite enjoyed working on Monday, where we pretty much had most of the day working on deliverables and digging through the archives on our own, so I am definitely looking forward to the project phase of the internship. I do expect however that I will run into mind-block situations similar to those that happened when working on text analysis as opposed to the other deliverables which have had much smoother brainstorming sessions. I also still don’t have any idea what shape or form my end project will end up taking but lets not come to that until we have to.