Musical Influence Network Analysis and Rank of Sample-Based Music
نویسندگان
چکیده
Computational analysis of musical influence networks and rank of sample-based music is presented with a unique outside examination of the WhoSampled.com dataset. The exemplary dataset maintains a large collection of artist-to-artist relationships of sample-based music, specifying the origins of borrowed or sampled material on a song-by-song basis. Directed song, artist, and musical genre networks are created from the data, allowing the application of social network metrics to quantify various trends and characteristics. In addition, a method of influence rank is proposed, unifying song-level networks to higher-level artist and genre networks via a collapse-and-sum approach. Such metrics are used to help interpret and describe interesting patterns of musical influence in sample-based music suitable for musicological analysis. Empirical results and visualizations are also presented, suggesting that sampled-based influence networks follow a power-law degree distribution; heavy influence of funk, soul, and disco music on modern hip-hop, R&B, and electronic music; and other musicological results.
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