Curatr: A Platform for Semantic Analysis and Curation of Historical
  Literary Texts
Susan Leavy Gerardine Meaney Karen Wade Derek Greene
The increasing availability of digital collections of historical and
contemporary literature presents a wealth of possibilities for new research in
the humanities. The scale and diversity of such collections however, presents
particular challenges in identifying and extracting relevant content. This
paper presents Curatr, an online platform for the exploration and curation of
literature with machine learning-supported semantic search, designed within the
context of digital humanities scholarship. The platform provides a text mining
workflow that combines neural word embeddings with expert domain knowledge to
enable the generation of thematic lexicons, allowing researches to curate
relevant sub-corpora from a large corpus of 18th and 19th century digitised
texts.