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SUBMIT YOUR IDEAThis is something I do often in Alteryx for interpreting open-ended survey responses!
I ran it through the Text-Pre-Processing tool for funsies as well to remove stop words, and the most common pertinent words were said, prince, pierre, time.
I was able to create the workflow reasonably easy the problem I had was determining what 'words' (or rather characters) where relevant. Initially I eliminated all numerics but then that may have left behind characters that may or may not be relevant. I was also not sure whether to drop hyphens but I left those in. Then there was case; is it a name or just the beginning of a sentence or just all uppercase for emphasis. In the end I realised that I just needed to use the old KISS approach and eh voila it worked.
Still it could be an interesting extended challenge (I'm sure it's already been done) to accurately count words, names, numbers and er junk.
Couldn't get exactly the same answer, but fun challenge. 😅
my solution: