Monday, November 12, 2018

Networks and success in art

S. P. Fraiberger et al., Quantifying reputation and success in art, Science 10.1126/science.aau7224 (2018).
Abstrarct: In areas of human activity where performance is difficult to quantify in an objective fashion, reputation and networks of influence play a key role in determining access to resources and rewards. To understand the role of these factors, we reconstructed the exhibition history of half a million artists, mapping out the coexhibition network that captures the movement of art between institutions. Centrality within this network captured institutional prestige, allowing us to explore the career trajectory of individual artists in terms of access to coveted institutions. Early access to prestigious central institutions offered life -long access to high -prestige venues and reduced dropout rate. By contrast, starting at the network periphery resulted in a high dropout rate, limiting access to central institutions. A Markov model predicts the career trajectory of individual artists and documents the strong path and history dependence of valuation in art.
From the article: 
Fig. 1. Coexhibition network. Force - directed layout of the order τ = ∞ coexhibition network, whose nodes are institutions (galleries, museums). Node size is proportional to each institution ’s eigenvector centrality. Nodes are connected if they both exhibited the same artist, with link weights being equal to the number of artists’ coexhibitions. Node colors encode the region in which institutions are located. Links are of the same colors as their end nodes, or gray when end nodes have different colors. For visualization purposes, we only show the 12,238 nodes corresponding to institutions with more than 10 exhibits; we pruned the links by keeping the most statistically significant links ( 20 ) (supplementary text S2.2). We implemented community detection on the pruned network ( 21 ), idendentifying 122 communities (supplementary text S2.30. We highlighted five of them, the full community breakdown being shown in fig. S3. We also show the names of the most prestigious institution for each community.

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