Music, Memory, and Computational Music Analysis: Two Coded Literature-Review Datasets (2020–2025)

This deposit contains two coded literature-review datasets supporting the 2026 MA thesis A Computational Model of Musical Working Memory: Software for Real-Time Multimodal Data Integration in Music and Interdisciplinary Research by Oğuzhan Tuğral, University of Massachusetts Amherst.

The first dataset examines music-and-memory research published between 2020 and 2025 and retrieved from PubMed and JSTOR. As reported in the thesis, it comprises 190 studies across 113 journals and 48 countries. Records include bibliographic information and coded descriptions of research backgrounds, problems, goals, methods, findings, and the treatment of musical material, including whether harmonic or melodic analysis is reported.

The second dataset surveys chord-recognition and music-tokenization research from arXiv, IEEE, and TISMIR over the same period. It documents analytical approaches, reliance on expert annotation, and characteristics of computational systems.

Together, the datasets support descriptive statistical analysis, categorical comparisons, and visualization of disciplinary and methodological patterns. They accompany Chapter 2 of the thesis, particularly Sections 2.1–2.2.4.

The deposit provides Excel snapshots of the source tables. These are literature-derived research records, not participant-level behavioral, physiological, or clinical data.