  The concept of literary genre is a highly complex one: not only are different
genres frequently defined on several, but not necessarily the same levels of
description, but consideration of genres as cognitive, social, or scholarly
constructs with a rich history further complicate the matter. This contribution
focuses on thematic aspects of genre with a quantitative approach, namely Topic
Modeling. Topic Modeling has proven to be useful to discover thematic patterns
and trends in large collections of texts, with a view to class or browse them
on the basis of their dominant themes. It has rarely if ever, however, been
applied to collections of dramatic texts.
  In this contribution, Topic Modeling is used to analyze a collection of
French Drama of the Classical Age and the Enlightenment. The general aim of
this contribution is to discover what semantic types of topics are found in
this collection, whether different dramatic subgenres have distinctive dominant
topics and plot-related topic patterns, and inversely, to what extent
clustering methods based on topic scores per play produce groupings of texts
which agree with more conventional genre distinctions. This contribution shows
that interesting topic patterns can be detected which provide new insights into
the thematic, subgenre-related structure of French drama as well as into the
history of French drama of the Classical Age and the Enlightenment.
