Skip to main content

Power Laws Reveal Pattern for Distribution of Artistic Talent

The paper I read entitled “Power Laws in Art” analyzed artistic works from the 1500s to contemporary time to determine whether there exists a general pattern for the distribution of artistic talent. The authors analyzed historical bid data ranging from secondary markets of Amsterdam during the 1600s to Parisian auctions in the 1700s and worldwide auctions covering the period of 1985 to 2016 for contemporary artworks. The researchers then used an average price of artists’ artworks to model a distribution of artistic talent. (The price of an artwork was assumed to reflect a measure of talent of the artist, as in the competitive secondary market, the prices of unique objects should reflect the max willingness to pay on the demand side.) Based on their research, the authors found evidence of a nearly cubic power-law tail in the distribution of artistic talent, which persists over centuries. This finding relates to what we learned in class regarding popularity, the rich-get-richer effect, and power-laws. The probability that the average price of an artist’s artworks increases (perceived talent of the artist increases) is directly proportional to the current price of the artist’s artworks.

In addition to this, the researchers looked at the relationship between masters and apprentices of art. They envisioned the teacher-student relationships as a network with 1906 nodes and a giant component that included 60% of links. The correlation between average prices for artwork of teachers and students was found to be positive (.15). This phenomenon can be explained by network theories discussed in class. If we envision students and teachers as nodes in a bipartite graph (with teacher nodes representing one set in the graph and student nodes the other and with edges indicating links between students and teachers), then the artistic value or talent others associate with a student should increase if he is linked to a valuable (talented) teacher, and for the more valuable students a teacher trains (more outgoing edges the teacher has to talented nodes), the teacher’s own value should also increase.


Leave a Reply

Blogging Calendar

November 2018