Art Metrics
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Success in art markets is difficult to quantify objectively, as it also relies on complex social networks and exchanges of reputation among different actors of the system. We discuss the general task of developing art metrics that are able to capture the different roles actors play in art markets, in particular artists and collectors, are time-aware and efficient to account for the dynamic nature of such markets, and are predictive of future success. As a first contribution in this direction, we propose a method to capture the mutually reinforcing role of artists and collectors via a time-aware extension of Kleinberg's HITS method, originally developed for the Web. We apply the method to a dataset comprising all the events of the crypto art gallery SuperRare during its first year of existence. Crypto art is limited-edition, collectible, and tradable digital art cryptographically registered on a blockchain. This very recent artistic movement, sharing several approaches and philosophies with conceptual art, is producing data at an unprecedented level of detail when compared to the traditional art market. The proposed method is predictive of future success and accurately captures the roles of artists and collectors.
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