finding themes from text documents
The best method to find themes in a collection of documents is topic modeling. Topic modeling finds the hidden (aka, latent) themes beyond just keyword counts. 

There are many approaches to topic modeling. Latent Dirichlet allocation (LDA) is a standard topic modeling approach. LDA is a probabilistic graphical model that assumes that each document is a mixture of a small number of topics and that each word's creation is attributable to one of the document's topics. The number of topics is a selected hyperparameter.