As with all NLP/machine learning, it's trivial to do if you know the tools and already have the data -- but pretty difficult to do well.
again, one person may be satisfied with a certain achieved result, but that may work not quite well for other person. just for instance, clusterization or topic extraction. you should have some knowledge about what you want to get, what are the possible outcomes of investigation, and dig into data to get what you need. generic approach will give broad resultset that may require some additional effort for real-world usage.