I have a dataset of responses where people were requested to answer a set of questions. There's only one column of text data to process.
My challenge is; only very few respondents have actually written long texts that I found easy to process and gain insights from it. Most of the other responses are often found to be very short such as "Somewhat", "Yes", "No", "Larger extent". That too, it has been not possible to scale it ordinally because there's no logical order to it.
I have been able to use the longer text responses to gain insights on Sentiments, extract keywords and phrases and apply Machine learning such as RAKE and PMI. I used UDPIPE library with R.
However, for shorter "few words" responses, I am finding it really difficult to gain insights from these.
Is there any other machine learning technique possible with the current issue I'm having ? Or do I need to try any NLP technique ?