I first experimented with word clouds several years ago and used them to visualise the speeches of Kevin Rudd and Malcolm Turnbull. I have now learned from the Fell Stats blog (via R-Bloggers) that there is an R package for generating word clouds. The package makes use of tm, a text mining package for R, which I have been meaning to look into for some time. So, it seemed only appropriate to explore the speeches of Tony Abbott.
This word cloud shows the 150 most-used words in Tony’s speeches over the last 18 years. Perhaps disappointingly, since my efforts to strip punctuation also stripped apostrophes, “cant” actually only shows the frequency of the word “can’t”.
Pretty though the word cloud is, a little more can be gleaned from the word usage patterns through time. The correlation in recent years between “carbon” and “tax”, is clearly due to Abbott’s attacks on Labor’s imposition of a price on carbon. His stint as health minister is also evident. I did expect to see more of an impact from his “stop the boats” campaign (here the count for “boat” includes “boats”).
Admittedly, there are no particularly deep insights here, but it was a fun way to learn about the tm and wordcloud packages.
UPDATE: In response to the comment from Dan, I have added a chart showing word frequency rather than count. This accounts for distortions arising from the larger number of Abbott speeches in recent years.
Abbott word frequency through time
For those who are interested, I have uploaded the (python) code for downloading the speeches and the (R) code for generating the charts to github.