I have an unlabelled data-set consisting of thousands of Wikipedia articles.

These articles are grouped into sets of articles that are closely related in terms of their content.

Given one of these sets, I want to determine the common topic(s) that all of its articles belong to.

Example:

Given the following set of related articles by their title:

{Calculus, matrices, number theory}

I can determine that a common topic is mathematics.

Is there a simple way to do this programmatically by analysing the text of each article?

It doesn’t need to be super accurate and precise.

If this is not possible, a list of words that most accurately represent the set of related articles should suffice.