BARABÁSILAB: HIDDEN PATTERNS BARABÁSILAB: HIDDEN PATTERNS
  • ART NETWORK (2018/2020) - 3. view
    BARABÁSILAB: HIDDEN PATTERNS HIDDEN PATTERNS CHOOSE VIEW ENTRANCE ENTRANCE - 2. view NATURE 150 (2019) NATURE 150 (2019) - 2. view NATURE 150 (2019) - 3. view FLAVOR NETWORK (2011) FLAVOR NETWORK (2011) - 2. view MOBILITY AND PANDEMIC (2008/2020) MOBILITY AND PANDEMIC (2008/2020) - 2. view CONTROL (2011) CONTROL (2011) - 2. view DISEASOME (2007) DISEASOME (2007) - 2. view INTERACTOME (2012) INTERACTOME (2012) - 2. view CONNECTOME (2019) CONNECTOME (2019) - 2. view HOT NETWORKS (2019) SKETCHES (2018) LIBRARY LIBRARY - 2. view VIRUSES (2009/2020) FAKE NEWS (2018) ART NETWORK (2018/2020) ART NETWORK (2018/2020) - 2. view ART NETWORK (2018/2020) - 3. view COSMIC WEB (2016) COSMIC WEB (2016) - 2. view IMPRESSUM
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ART NETWORK (2018/2020) - 3. view

Grpah V.

ART NETWORK (2018/2020) - 3. view

The network map of the global (local) art scene 

In 2016, Barabási began turning the tools of network and data science, which his lab had been honing for two decades already, on the art world. He started with a massive number of data points about the exhibition history of half a million artists in galleries and museums worldwide that had been collected by Magnus Resch, an economist and entrepreneur, who studies the art market. The data enabled the BarabásiLab to unveil the invisible connections that shape artists’ careers.

In The Art Network, two institutions—for example, a museum and a gallery—are connected if an artist whose work was exhibited at the museum is also exhibited next at the gallery. The map exhibited in the large hall captures the largely invisible network of influence and trust between thousands of institutions worldwide. 

For us, though the main interest lies with the local art scene, the network of the Eastern European, and in particular the Hungarian, art world. Mapping it accurately is one of the projects carried out in preparation for the exhibition. The creation of the Hungarian Art Network was preceded by several months of data collection and data cleaning by a volunteer team with background in both art and data science. In the course of this project, a comprehensive database was created, relying primarily on the art databases of ikOn, artportal and ArtFacts. Different versions of this map can be seen in the exhibition: the network of Hungarian artists (in two 2D print versions, a 3D installation shown at the museum’s staircase, and a virtual reality 3D sculpture), the network of Hungarian art institutions and the network of curators, as well as the individual institutional network of a hundred Hungarian artists, drawn by a robot each day. Finally, the collected data allowed the team to rank over 900 Hungarian artists with six different measures of success. All six ranking lists are shown, to illustrate that success in art has multiple dimensions.