all our analyses are based on econometric methods of network theory.
collecting data base.
A very high proportion of artists, galleries, and other people and institutions active in the art market use social media to discover, dicuss or comment on art. The most relevant social media platform in the art world is Instagram. Even if an artist is not active on social media, this does not mean that the artist is absent on social media. Other people will create content using the “hashtag” function linking to a given artist. These social media platforms contain an enormous amount of usable information. In order evaluate the information hidden in these mountains of data, we use methods of quantitative network theory appropriate to the analysis of digital networks.
In order to approximate reputation we create our proprietary attention index that shows how much digital attention an artist, gallery or museum gets over time from relevant people and institutions in the global art market. Each person and institution in our global hub of art market relevant players (more than 250’000 nodes) is ranked with our proprietary AMIS score (Art Market Importance Score).
The attention index is high when many relevant people and institutions interact with the artist or the gallery, whose attention is being measured. People and institutions that are not part of the defined art hub cannot influence the index.
In quantitative network theory, a network, like an art hub, is translated by means of a so-called adjacency matrix. The adjacency matrix translates a real network into a mathematical entity, which can be used to calculate network statistics. This matrix also describes various characteristics, such as the centrality of the individual people or institutions in the network.