Music in the Data

Putting forward an extensive new argument for a humanities-based approach to big-data analysis, The Music in the Data shows how large datasets of music, or music corpora, can be productively integrated with the qualitative questions at the heart of music research. The author argues that as well as providing objective evidence, music corpora can themselves be treated as texts to be subjectively read and creatively interpreted, allowing new levels of understanding and insight into music traditions.

Each chapter in this book asks how we define a core music-theory topic, such as style, harmony, meter, function, and musical key, and then approaches the topic through considering trends within large musical datasets, applying a combination of quantitative analysis and qualitative interpretation. Throughout, several basic techniques of data analysis are introduced and explained, with supporting materials available online. Connecting the empirical information from corpus analysis with theories of musical and textual meaning, and showing how each approach can enrich the other, this book provides a vital perspective for scholars and students in music theory, musicology, and all areas of music research.

Winner, Emerging Scholar Award (Book), Society for Music Theory, 2023