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社交信号比视觉特征更能预测当代艺术作品的价格,在新兴市场尤其如此。

Social signals predict contemporary art prices better than visual features, particularly in emerging markets.

作者信息

Lee Kangsan, Park Jaehyuk, Goree Sam, Crandall David, Ahn Yong-Yeol

机构信息

Division of Social Science, New York University Abu Dhabi, Abu Dhabi, UAE.

School of Public Policy and Management, Korea Development Institute, Sejong-si, Republic of Korea.

出版信息

Sci Rep. 2024 May 21;14(1):11615. doi: 10.1038/s41598-024-60957-z.

Abstract

What determines the price of an artwork? This article leverages a comprehensive and novel dataset on art auctions of contemporary artists to examine the impact of social and visual features on the valuation of artworks across global markets. Our findings indicate that social signals allow us to predict the price of artwork exceptionally well, even approaching the professionals' prediction accuracy, while the visual features play a marginal role. This pattern is especially pronounced in emerging markets, supporting the idea that social signals become more critical when it is more difficult to assess the quality. These results strongly support that the value of artwork is largely shaped by social factors, particularly in emerging markets where a stronger preference for "buying an artist" than "buying an artwork." Additionally, our study shows that it is possible to boost experts' performance, highlighting the potential benefits of human-machine models in uncertain or rapidly changing markets, where expert knowledge is limited.

摘要

是什么决定了一件艺术品的价格?本文利用一个关于当代艺术家艺术拍卖的全面且新颖的数据集,来研究社会和视觉特征对全球市场上艺术品估值的影响。我们的研究结果表明,社会信号能让我们非常准确地预测艺术品价格,甚至接近专业人士的预测准确率,而视觉特征所起的作用微不足道。这种模式在新兴市场尤为明显,这支持了以下观点:当评估质量变得更加困难时,社会信号就变得更加关键。这些结果有力地支持了艺术品的价值在很大程度上是由社会因素塑造的,特别是在新兴市场,那里对“购买艺术家”的偏好强于“购买艺术品”。此外,我们的研究表明提高专家的表现是可能的,这凸显了人机模型在专家知识有限的不确定或快速变化的市场中的潜在益处。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/57b1/11109285/3d5245d9da8b/41598_2024_60957_Fig1_HTML.jpg

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