Determining interests from Twitter text using Latent Dirichlet Allocation
Thanks for your comments, reformulating the question lead me to a different way of thinking about the problem.

Getting an interest category list is actually reasonably straightforward for broad level hobbies it is just the labelled training data that may be hard to produce.

I found this paper on unsupervised text classification and this is probably a better fit than topic models in this scenario. It uses a small number of keywords (average 3) per category and segmented sentences to produce training data for a naive Bayes classifier. 

I think I will use this with some Twitter specific text pre-processing and some sentiment classification to see if the categories are spoken of in a positive light.