D’Artagnan earns his Musketeer blue.

Cardinal red.

If you follow me on Twitter, you may have noticed recently that I took to tweeting excerpts from Alexandre Dumas’s novel The Three Musketeers interspersed with sarky commentary.  (Flourish of the plumed hat to my friend Dr Jem Bloomfield for goading me on in this dubious literary venture.)  It is a document that rather lends itself to the layering on of innuendo where none was originally intended. (Okay, some was originally intended.  But not as much as I managed to find in it.)  I had so much fun doing this that I decided to capture all the tweets and preserve them somewhere.

The obvious choice for a collection of tweets would be Storify, but they don’t offer any kind of privacy settings for free accounts.  Strange as it may seem, dear reader, when my blog tagline is ‘frequently a bit silly’, there are actually still some places on the internet that I’d like to preserve a modicum of professional decorum and Storify is one of them.  Right now all my Storify creations are collections of information from past conferences–it’s become a little portfolio, almost–and I’d rather not muddy the waters with a tittering exegesis of swashbuckling 17th century roisterers.  If there were a way to group stories into different categories I might still consider publishing the MusketeerTweets Storify, but as things are I’ve decided not to.  [Edit: I did also try to embed them in this blog, where I do have some category control, but the embed function includes the post you’re embedding and some but not all of the replies, so it didn’t look like a neat, continuous stream in the way that Storify does.] If you are a Person of the Internet who has similarly struggled with the conflict between different presentational selves in different areas of digital life I would really love to hear your thoughts about this.

All is not lost, though: I was able to use my collection of tweets to do some basic word frequency analysis by using some simple free tools.  Bear in mind this is the frequency of the words in my collection of commentary tweets rather than that in the novel itself.  So basically it’s a rather egocentric mind map of the bits of the novel that made the biggest impression on me personally.  Fortunately Wordle lets you make word frequencies into graphics.  (I’ve ignored some common words like ‘it’, ‘he’, ‘and’, etc. for those digital methods fans out there. [Edit: And this morning I noticed that I’d done silly things like excluding ‘is’ but not ‘be.’  This is what comes of a hastily assembled data set.  Consider this a musketeery lesson in data quality.])  ‘Infographic’ might be stretching it just a little in this case, as they only information you’re getting is the inner workings of my brain, but they were fun to assemble nonetheless.

I could imagine using a tool like this to conduct a hybrid quant-qual project with a bigger sample (more than just one person!) that as part of its research outcomes would assemble either a single word cloud or a series of word clouds based on aggregate responses to a particular text.  This could be a simple but very visually effective way of representing personal relationships with the written word.