You can train a supervised model, taking into account the properties of the rater as well as the artwork, and tease out the factors that make it rated so.
You can probably cluster raters and the artwork they rate highly - but probably not in large quantities? -- Which might be the case also with raters being willing to tell you why - and how! most love to do that - but also not in very large quantities. With the added issues that the raters' own opinion of why they love or hate something is likely not to be entirely true and self-understanding.
You could use a larger corpus, like auction house files and art magazines. But then you are confounding for celebrity - a large ingredient in art prices.
