I have textual data for responses from people in the US and Canada pertaining to questions around how they feel about their experience using a certain product. I’ve used the Topic Extractor and can’t really see any differences. I’m wonder if there is a way to statistically compare the male vs. female to see what the big topic differences are…versus me trying to speculate based on topics.
one thing that you could try is to train a predictive model that distinguished between male and female comments. If the model accuracy is good e.g. >80% than this is a clear indicator, that these comments are different and can be separated well. If you use a predictive model that you can read e.g. a decision tree you can even check the features (terms) that are use for separation. These features can give you an indication about the topics.
I hope this helps.
Thanks Kilian. I will do some research on this approach and test it out.