Quantifying reputation and success in art

Samuel P. Fraiberger, Roberta Sinatra, Magnus Resch, Christoph Riedl, Albert-Ĺaszló Barabási

Science · 2018 · 212 citations · 17 references

Concepts

TL;DR

Reputation and influence networks determine access to resources when performance is hard to quantify. The study reconstructs half a million artists’ exhibition histories to map a coexhibition network of art movement between institutions. Centrality in this network captures institutional prestige, enabling analysis of artists’ career trajectories, and a Markov model predicts these trajectories, revealing strong path and history dependence. Early entry into prestigious central institutions yields lifelong access and lower dropout, while peripheral starts lead to higher dropout, and the Markov model confirms strong path and history dependence in artist valuation.

Abstract

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.

References

17