The Multi-Scale Network Landscape of Collaboration

TL;DR

This paper introduces new methods to analyze the complex, multi-scale collaboration network of classical musicians, revealing patterns that reflect cultural diversity and individual artistry.

Contribution

It presents novel analytical techniques for multi-scale network analysis applied to a large-scale musician collaboration dataset, uncovering meaningful cultural and individual patterns.

Findings

Identification of multi-scale collaboration patterns

Revealing diversity of cultural styles

Highlighting individuality of artists

Abstract

Propelled by the increasing availability of large-scale high-quality data, advanced data modeling and analysis techniques are enabling many novel and significant scientific understanding of a wide range of complex social, natural, and technological systems. These developments also provide opportunities for studying cultural systems and phenomena -- which can be said to refer to all products of human creativity and way of life. An important characteristic of a cultural product is that it does not exist in isolation from others, but forms an intricate web of connections on many levels. In the creation and dissemination of cultural products and artworks in particular, collaboration and communication of ideas play an essential role, which can be captured in the heterogeneous network of the creators and practitioners of art. In this paper we propose novel methods to analyze and uncover meaningful patterns from such a network using the network of western classical musicians constructed from a large-scale comprehensive Compact Disc recordings data. We characterize the complex patterns in the network landscape of collaboration between musicians across multiple scales ranging from the macroscopic to the mesoscopic and microscopic that represent the diversity of cultural styles and the individuality of the artists.