Author: Valeria Kolycheva, Dmitry Grigoriev, Alexander Semenov, Arsenii Pimenov and Taisia Pimenova
Title of host publication: Computational Data and Social Networks: Proceedings of the International Conference on Computational Data and Social Networks, 2024
Abstract: Online reviews play a crucial role in determining the price of goods, and the art market is no exception. However, due to the varying levels of expertise and influence among participants, it is essential to analyze each group separately. In this work, we explore the influence of experts and public sentiment on painting prices. To investigate this, we employ a hedonic regression model with fixed effects for artists. Our dataset comprises 18,100 sold paintings at Sotheby’s, Christie’s and Phillips auction houses. Additionally, we examine the relationship between review sentiment and buyers’ investment intentions, as purchasing paintings as an investment is a widespread practice in the secondary art market. Our results indicate that negative opinion from various sources and positive public opinion significantly influence the price of paintings in line with their respective valence. Furthermore, we observe that negative opinion from experts and news publications has a more pronounced effect on pricing. Our findings contribute to empirical research on the price determinants of artworks and examining online reviews from different sources.
Title of host publication: Computational Data and Social Networks: Proceedings of the International Conference on Computational Data and Social Networks, 2024
Abstract: Online reviews play a crucial role in determining the price of goods, and the art market is no exception. However, due to the varying levels of expertise and influence among participants, it is essential to analyze each group separately. In this work, we explore the influence of experts and public sentiment on painting prices. To investigate this, we employ a hedonic regression model with fixed effects for artists. Our dataset comprises 18,100 sold paintings at Sotheby’s, Christie’s and Phillips auction houses. Additionally, we examine the relationship between review sentiment and buyers’ investment intentions, as purchasing paintings as an investment is a widespread practice in the secondary art market. Our results indicate that negative opinion from various sources and positive public opinion significantly influence the price of paintings in line with their respective valence. Furthermore, we observe that negative opinion from experts and news publications has a more pronounced effect on pricing. Our findings contribute to empirical research on the price determinants of artworks and examining online reviews from different sources.