This article provides an example of the successful integration of text and data mining (TDM) into the Research Methods for Performers course, a required course for students in the Keyboard Collaborative Arts (KCA) Master of Music (MM) program at Chapman University. This course is similar in scope and content to the course frequently titled Music Bibliography at other institutions, and the methods described also apply to such courses. Incorporating TDM into this course effectively introduced data-focused research methods to performing arts students and expanded the students’ understanding of the scope and possibilities of research in music through the application of digital humanities in the study of music.
This case study will present the author’s perspective as an instructor with a music librarianship background, not from the position of an experienced data scientist. The focus is primarily pedagogical and concerns teaching students from a music background, so it does not contain highly technical concepts, programming information, or detailed data analysis. Although this case study is from an instructor’s perspective, the methods are also relevant to librarians seeking a pathway to enhance their library instruction and research assistance skill set.
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Greene, T. J. (2024). Text and data mining for pianists? Bringing digital humanities to a graduate music research methods course through topic modeling. Music Reference Services Quarterly. https://doi.org/10.1080/10588167.2023.2293602