Exploring the music library association mailing list: a text mining approach

Abstract

Music librarians and people pursuing music librarianship have exchanged emails via the Music Library Association Mailing List (MLA-L) for decades. The list archive is an invaluable resource to discover new insights on music information retrieval from the perspective of the music librarian community. This study analyzes a corpus of 53,648 emails posted on MLA-L from 2000 to 2016 by using text mining and quantitative analysis methods. In addition to descriptive analysis, main topics of discussions and their trends over the years are identified through topic modeling. We also compare messages that stimulated discussions to those that did not. Inspection of semantic topics reveals insights complementary to previous topic analyses of other Music Information Retrieval (MIR) related resources.