Research in Music & Statistics
"Prince, what you are, you owe to chance and birth; what I am, I owe only to myself. Princes have and always will exist in their thousands -- of Beethoven, there is only one." (Beethoven to Count Lichnowsky)
Some of my articles applying statistics to classical music, composers, and music manuscripts:
Georges, P. and A. Seckin. (2022). "Music Information visualization and classical composers discovery: an application of network graphs, multidimensional scaling, and support vector machines." Scientometrics, Volume 127 (5), pp. 2277-2311. Open Access article
Georges, P. (2020). "Music Information: Classical Composers Networks and Similarities." Topic-contributed paper for Session on: ‘Statistics and Artificial Intelligence in Music’, 2020 Joint Statistical Meetings of the American Statistical Association.
Georges, P. and N. Nguyen. (2019). "Visualizing music similarity: clustering and mapping 500 classical music composers." Scientometrics, Volume 120 (3), pp 975–1003. Open Access article
Georges, P. (2017). "Western classical music development: a statistical analysis of composers similarity, differentiation and evolution." Scientometrics, Volume 112(1), pp 21–53. Open Access Article
Smith, C.H., Georges, P., and N. Nguyen (2015). “Statistical Tests for 'Related Records' Search Results.” Scientometrics. 105(3), 1665-77, 2015. Article
Smith, C.H. and P. Georges. (2015). “Similarity Indices for 500 Classical Music Composers: Inferences from Personal Musical Influences and ‘Ecological’ Measures.” Empirical Studies of the Arts, 33(1), 61-94. Article
Smith, C.H. and P. Georges. (2014). “Composer Similarities through ‘The Classical Music Navigator’' -- Similarity Inference from Composer Influences.” Empirical Studies of the Arts, 32(2), 205-229.Article
Georges, P. and A. Seckin. (2013). “Black Notes and White Noises: A Hedonic Approach to Auction Prices of Classical Music Manuscripts.” Journal of Cultural Economics, 37(1), 33-60. Article
A. Maps of European Art Music/composers (based on MDS methodology, Georges and Nguyen, 2019)
1. European art music. Seven centuries in one graph. An application of the MDS methodology
2. The Baroque Period: An application of the MDS methodology
3. The Classical Period: An application of the MDS methodology
4. The Romantic Period: An application of the MDS methodology
B. Dendrograms depicting the 'intra-period evolutions' of European art music
1. Baroque Period
2. Classical Period
3. Romantic Period
C. K-means clustering of 65 composers (K= 5 clusters)
