Several weeks ago, I posted an analysis of tweets about the restrictions imposed on Melbourne residents in an effort to control an outbreak of Covid-19. That analysis was essentially a road-test of a Knime workflow that I had been piecing together for some time, but that was not quite ready to share. Since writing that post, I have revised and tidied up the workflow so that anyone can use it, and I have made it available on the Knime Hub.
In the present post, I provide a thorough description of the workflow, which I have named the TweetKollidR, and demonstrate its use through a case study of yet another dataset of tweets about Melbourne’s lockdown (which, as I write this, still has not ended, although it has been eased). 1
Continue reading TweetKollidR – A Knime workflow for creating text-rich visualisations of Twitter data
- As you will see from the search queries in Figure 3, this dataset includes some keywords that relate to Victoria more generally, rather than just Melbourne. However, since most of the content concerns the Melbourne lockdown, I will continue to refer to it as such. ↩