Correlation between words, then texts
One method you can try first is cosine similarity. It works by counting the number of occurrences of each word in the vocabulary for each individual document. Next, you put these counts into vectors and then you take the cosine of the angle between them. 

If you have more than one text on a topic, you can combine them into a single text for the purpose of finding the cosine similarity between various topics. 

If you have many texts that are examples of each topic, then you can create a supervised machine learning model. However, since your purpose is interpretation instead of prediction, I would recommend a technique like cosine similarity before getting insight from interpreting a predictive model.