Music Theory Spectrum

759 papers and 4.8k indexed citations

About

The 759 papers published in Music Theory Spectrum in the last decades have received a total of 4.8k indexed citations. Papers published in Music Theory Spectrum usually cover Music (571 papers), Computer Vision and Pattern Recognition (282 papers) and Cognitive Neuroscience (266 papers) specifically the topics of Musicology and Musical Analysis (528 papers), Music Technology and Sound Studies (281 papers) and Neuroscience and Music Perception (264 papers). The most active scholars publishing in Music Theory Spectrum are Carol L. Krumhansl, Robert Morris, Nicholas Cook, Nicole Biamonte, Jacob Straus, Christopher Hasty, Richard Cohn, Norman Carey, David Clampitt and Peter H. Smith.

In The Last Decade

Music Theory Spectrum

476 papers receiving 2.3k citations

Countries where authors publish in Music Theory Spectrum

Since Specialization
Citations

This map shows the geographic impact of research published in Music Theory Spectrum. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by papers published in Music Theory Spectrum with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Music Theory Spectrum more than expected).

Fields of papers published in Music Theory Spectrum

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Music Theory Spectrum. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers published in Music Theory Spectrum.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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