Classifying survey response text SVM I have 800 responses to an open-ended survey question. Each response is categorized into 3 categories based on a list of 70 categories. These categories are things like "stronger leadership", "better customer service", "programs", and etc...

My question is, can I use this as a training data set in order to develop a model that I can use in the future as we get more survey responses? We would like to be able to tag, label, or classify each survey response into (up to) 3 of the 70 categories.

Is this even possible? Or do I have to use a NB with simple words? Can you please guide me to tutorials, examples, etc.?

Using R in this exercise.
Can you clarify what you're trying to predict with these responses?

My initial reaction is that with open-ended surveys you'll have a tough time implementing classification algorithms. Open-ended-ness means you don't have a finite feature space and thus you can't do the usual transformation of responses into a feature matrix.

However, there may be other ways to make this work. If you have 5 questions, for instance, you may be able to use sentiment analysis or other methods to come up with metadata about the open ended response that can help you design a classification scheme.