Tweet Clouds

I have a confession to make — I grew bored of Twitter after a couple of days.
However, I felt obliged to keep on Twittering something… anything… so I hooked our OPAC into the feed instead. Every 5 minutes, a bit of code checks to see what the most popular keyword(s) used on our OPAC has been recently and, if it’s different to the last run, it fires it off to Twitter. I was so lazy, I didn’t even bother filtering out stopwords.
The result is an eclectic mix of words that encapsulate our student’s usage of the library catalogue — little snapshots of what was important to a bunch of students (or perhaps one particular determined student). Topics meander semi-randomly, occasionally repeating at unusual intervals.
Sometimes, there’s not a single popular keyword, but several. Sometimes the multiple words make sense, other times they create weird phrases…

  • british genetics music
  • angina attachment theatre
  • education picasso sex
  • rape skills study

Anyway, a few days ago I spotted Tweet Clouds and decided to see what it made of my feed…
…and here’s a cloud I made back in December 2006
I must admit, I feel kinda guilty that I ate up 23 minutes of CPU time on the Tweet Cloud site :-S

"Spin, spin, spin the Wheel of Justice…"

Kudos if you automatically sang to yourself “…see how fast the bastard turns” 😉
If you’ve no idea what I’m on about, then YouTube is your friend.
Anyway, I got to playing around with the OPAC keyword cloud data and ImageMagick and came up with this (reload that web page to get a new image)…
wheel4 wheel3 wheel5 wheel10 wheel8 wheel11 wheel13 wheel12
I was struggling to remember how to find the points on the circumference of a circle until I remembered that one of the chapters in the original ZX Spectrum manual covered the topic.
The word in the middle is chosen at random from the top 200 most popular keywords used on our OPAC and the surrounding words at those most commonly used with that word.

OPAC keyword cloud

This is crying out to be done like the visual word map in AquaBrowser, but here’s a browseable tag cloud based on data from nearly 2 million keyword searches on our OPAC.
shakespeare performance
The code looks for other keywords that were entered as part of the same search (e.g. “ethics of nursing care”) to draw out the most commonly used words. For example, the most common keyword used with “performance” is “management”. The size of the word in the cloud is determined by how often it appears with the search keyword.
I’ve not removed keywords that generated zero search results, so the cloud for “acrobat” includes “abode”. (I’ve now removed zero result searches)
I’ll have to have a play to see if there’s a way of incorporating the cloud into the OPAC — for example, if you used a vague/general keyword such as “health“, then maybe the OPAC could suggest more specific searches for “health care”, “mental health” or “health promotion”?