Evaluation of verbal user ratings
I started experimenting with Rapid Miner a few days ago and now have a question. As data input, I use an Excel file with 100 written reviews for an app. I have already managed to process the data and arrange it in CLuster. Now I want to go a step further and expand the detailing.
As an an example for the input data:
User A: "I like the app very well"
User B: "The app does not work, no connection"
User C: "The app crashes."
Now I would like the data to be roughly represented as follows:
User A: like app
User B: Does not work, no connection
User C: app crashes
It should therefore be searched for common terms and then each be assigned as the keyword of the corresponding rating. Can you tell me if such a thing is possible and if so how can I do this best?