University College London (UCL) owns a large corpus of the philosopher and social reformer Jeremy Bentham (1748-1832). Until recently, these papers were for the most part untranscribed, so that very few people had access to the corpus to evaluate its content and its value. The corpus is now being digitized and transcribed thanks to a large number of volunteers recruited through a crowd-sourcing initiative called Transcribe Bentham (Causer and Terras, 2014a, 2014b). The problem researchers are facing with such a corpus is clear: how to access the content, how to structure these 30,000 files, and how to get relevant access to this mass of data? Our goal has thus been to produce an automatic analysis procedure aiming at providing a general characterization of the content of the corpus. We are more specifically interested in identifying the main topics and their structure so as to provide meaningful static and dynamic representations of their evolution over time.