Word clouds for textual analysis

Word clouds, including the pretty ones produced by Wordle (see right) can be a useful first step in analysing textual data. I regularly trawl through free text responses to surveys, looking for themes and patterns. By first creating a word cloud, which shows words used most frequently in a larger size, I get an idea of what to look for and how to categorise responses.

For example, the word cloud in this post is from textin response to a question asking students about the benefits of using wikis. From the cloud, I was able to instantly see some themes, and I could then go through and categorise the comments a little more methodically with the help of the keywords suggested by the cloud. The word clouds can also liven up any report or presentation made using the data.


Word clouds are not perfect, or even very scientific, for this kind of text analysis: they do not show the context in which the words were used (it could have been poor or good in front of the word 'access in the above example) and and don't account for similes (there may only be one word that corresponds to access, but several that represent organisation). A semantic word cloud, that recognised context and similes would be very powerful. There is a very nice prototype called 'concordle' (produced by Ladislav Kocba) that shows one way that context can be accounted for in a word cloud to produce a useful concordancing tool (very useful for textual analysis).

In fact, the survey software I use (Bristol Online Survey) produces word clouds, but not as prettily as Wordle does. If you use Wordle for this kind of analysis, beware that data you save is no longer yours. For this reason, when I use Wordle, I paste the data, take a screenshot of the wordcloud and then close without saving the resultant word cloud.

Google Docs also produced Word Clouds, and the spreadsheet forms can be used as a survey tool. There are lots of possibilities for gathering data and publishing clouds online through Google Docs. I plan to experiment with the possibilities this offers.

A former colleague, Andy Ramsden at Bath, uses word cloud as a way of aggregating textual responses gathered during a live presentation by getting the audience to text him from their phones, and then cutting and pasting the results into a word cloud generator. Word clouds are great for quick and dirty presentation of texts. Word clouds have lots of uses beyond making pretty pictures, or tag clouds at the side of a blog.

Voting systems still working for Durham Psychology Department

The Psychology department were amongst the more enthusiastic adopters of classroom voting systems at Durham University. I'm pleased to hear that they are still making good use of the 'clickers' a few years on. The usage pattern followed the usual Gartner curve from enthusiastic adoption and early experimentation, before settling into a model of continued use. They found a range of uses for them, from seeding discussion to collecting data. One lecturer adds to their research data set every time they present their results by gathering more data from the audience in the course of the presentation. They are also using them in outreach activity to schools, and on Open days to show the range of teaching techniques they employ.

Pedagogically, they ensure interaction for the whole class, and helps the teacher to adjust teaching based on what the students know. For example, one lecturer asked a difficult question at the beginning of the course to see what the students knew. The answers ranged from those expected from a novice, to those expected from someone who had passed the course. To his surprise, most chose the response expected at the end of the module! he had to adjust his teaching for the rest of the course, following the same outline and towards similar outcomes, but in a different way more in keeping with the student's understanding.