Crypto art identifies rare digital artworks associated with unique and provably rare tokens that exist on the blockchain. The concept is based on the idea of digital scarcity, which allows you to buy, sell, and trade digital art as if it were physical. Popular early examples include CryptoKitties, CryptoPunks, Rare Pepe, CurioCards, and (Bailey 2017, 2018).

Art curator Jason Bailey identifies a series of common factors that have shaped the aesthetic and community thus far (Bailey 2018):

  1. digitally native: artwork can be created, editioned, bought, and sold digitally;
  2. geographically agnostic: artists participate from all over the world;
  3. democratic: everyone is encouraged to participate;
  4. decentralized: tools and guidelines are designed to reduce the power of gatekeepers and middlemen and increase the autonomy of artists;
  5. anonymous: use of pseudonyms allows artists and collectors to create, sell or buy art while staying anonymous (if preferred);
  6. memetic: crypto artworks are often literally memes valued for their ability to spread quickly;
  7. self-referential: crypto artists often play with references to key events and personalities within cryptocurrency and blockchain culture;
  8. crypto patrons: crypto art is often collected by a group of savvy technologists and investors who got into cryptocurrency early;
  9. pro-artist: blockchain platforms often take little to no commission from artists; artists are often remunerated for every future sale of a single work;
  10. dankness: literally anyone can make something highly expressive or potent even if they have zero training.

Crypto art draws its origins from conceptual art (Lippard 1973): sharing the immaterial and distributive nature of artworks, the tight blending of artworks with currency, and the rejection of conventional art market and institutions. Many characteristics that were endemic to Duchamp’s practice, and later conceptual art in the 1960s and 1970s, are now visible in the immaterial and distributive logic of crypto art. See (Finucane 2018) for a parallelism between conceptual and crypto art and (Franceschet et al. 2020) for a crypto art position paper written by artists, collectors, gallerists, art historians and data scientists.

The status of an actor in a social context is determined by two factors: the total number of endorsements the actor receives from other actors and the prestige of the endorsing actors (Hubbell 1965). We cite from Johan Bollen (2006) the following example:

An author of pulp detectives may sell many books, but may not have earned the respect of literary critics. Conversely, a Nobel Prize in Literature winner may be highly valued among literary experts, yet never make the New York Times bestseller list.

Similarly, in bibliometrics, the status of a journal, of an article or of a scholar in the academic setting is commonly defined in terms of the number of citations received by other journals, articles or scholars (known as popularity) as well as in terms of the importance of the citing actors (known as prestige). In bibliometrics, it has been observed that prestige and popularity typically do not overlap significantly (Franceschet 2010).

In the context of (crypto) art, an artwork can be endorsed in different ways: by placing a bid on the artwork, by purchasing it, by casting a like or simply by viewing the artwork. All these are signals of market success for the art piece. On the other hand, the same artwork can be praised by art experts. We refer to this different kind of endorsement as prestige.

We are interested in investigating if success and prestige are strongly associated in the context of the new artistic trend known as crypto art. To this end, we concocted the following experiment. The role of art curators is to inform and arrange artistic content in a structured way so that the story behind a collection of artworks or artefacts can be communicated at different levels. We invited art curators and crypto artists to make a selection of artworks on the digital gallery SuperRare. One of the major crypto art galleries, SuperRare was born in April 2018. At the writing time the gallery features 7,125 artworks, more than half sold at least one time with an average resale value of +895%, for a value of 446,626$ earned by more than 200 artists. Nine crypto art curators and nine crypto artists accepted to participate to the research, namely:

We asked these actors to enter the SupeRare gallery with a blank mind and select 10 works (among 4585 artworks) published in the gallery before 15th September, 2019 that would be worth saving for future generations according to their curatorial taste, while justifying their choice. We explicitly requested artists not to choose their own works. Moreover, we invited all actors to make their choices regardless of the market success of the artworks, evaluating only the intrinsic quality of the works.

The collected data (artwork selection and motivations) have been processed as follows. First, we make a word frequency analysis on the text that curators and artists used to motivate their choices. This allowed us to identify important topics for both curators and artists, and to cast a first separation line between the two roles (art experts and art creators). Then, we correlated the choices made by the group of experts and artists with metrics of success of artworks in the SuperRare marketplace, hence investigating the association between prestige and success in the context of crypto art. This also allowed us to further investigate how the curatorial role differs from that of an artist.

For all analyses in this work, we used tidyverse R packages for data science and tidytext R package for text mining (Wickham and Grolemund 2017; Silge and Robinson 2017).

Exploring Artwork Selections

We start our investigation by exploring the selections made by curators and artists. Artworks are identified by their token id, a number from 1 to 4585, where smaller numbers correspond to older pieces. Artworks chosen by curators are well-distributed over the life of the gallery, with a peak in the initial stages of the gallery development. The median token number is 2006 (over 4585 tokens). The age of artworks chosen by artists has two peaks, old and new artworks, while tokens in the middle of the gallery life are rarely chosen by artists. The median token number is 1757.

We now give the ranking of artists chosen by at least three curators and that of artists chosen by at least three artists. For each artist, the nominators variable is the number of curators (or artists) that chose an artwork of the artist, and the nominations variable is the number of artworks of the artist chosen by curators (or artists). The compilation is sorted by nominators and then nominations.

Artists chosen by at least three curators
username nominators nominations
DrBeef_ 6 9
Hackatao 6 7
opheliafu 4 5
HEX0x6C 3 6
coldie 3 3
LoveArtHate 3 3
triplecode 3 3
Artists chosen by at least three artists
username nominators nominations
DrBeef_ 6 7
Hackatao 6 7
coldie 4 5
HEX0x6C 4 4
oficinastk 4 4
saito 4 4
artonymousartifakt 3 5
Roses 3 5
Kryptocromo 3 4
triplecode 3 4
opheliafu 3 3

Word frequency analysis

We make a word frequency analysis on the text that curators and artists used to motivate their choices:

  • the most used word by curators is viewer, followed by political, ai and love;
  • on the other hand, the most popular word among artists is love, closely followed by ai. Notably, the words political and viewer are never used by artists.

The word viewer used so often by curators always refers to the actor viewing the artwork, for instance it is used in sentences like “invites the viewer to think up a story” or “the artwork makes the viewer become part of the image”. It is a clear reference to the interest of art curators in the effect of the artwork on the observer. Also, the frequent use of the word political by curators is symptomatic. It is included in contexts such as “their work is utterly political” and “he deals with political and important issues of our time”. Curators are, evidently, quite attracted by artworks expressing a political view. Interestingly, these two terms, viewer and political, are never used by artists. Significant artworks for artists express emotions, not political opinions, in particular love and beauty. Also, the term AI (Artificial Intelligence) is quite popular among artists as well as curators. This refers to the recent (ephemeral?) stream of artworks that are made by training neural networks.

Comparing Prestige and Success

In this part we investigate if there is a correlation between prestige and success of an artwork. We say that:

  • an artwork is prestigious if it is endorsed by art experts as a remarkable piece of art;
  • an artwork is successful if it is endorsed by art collectors as a remunerative piece to buy.

Hence, do prestigious artworks have also market success? To answer this question, in collaboration with SuperRare gallerists, we isolated different signals that determine the commercial success of an artwork:

  1. market: the price amount of all sales and bids made by the artwork (on primary and secondary SuperRare market). The amount is expressed in fiat money using the exchange rate (according to of the time of the event (sale or bid);
  2. artist: the importance of the artist that created the artwork, measured as the overall amount of sales made by the artist. Again, the amount is expressed in fiat money using the exchange rates of the sale times;
  3. popularity: the number of likes and views collected by the artwork on the gallery website;
  4. speed: the speed of the first incoming bid that the artwork received, relative to the artwork creation time.

We define TokenRank as an overall artwork rating considering the above facets with different weights. In particular, the metric TokenRank is obtained as follows:

  1. for each facet (market, artist, popularity and speed) we extract the percentile of the token facet within the gallery facet distribution. The percentile is a number between 0 and 1, the higher the better for the token. For instance, a percentile of 0.75 for a facet of a given token means that 75% of the tokens in the gallery have a lower value for that facet. We used a percentile approach since we observed that the facet distributions are highly right-skewed;
  2. the final rating is then defined as the weighted mean of the 4 percentile facets using the following weights: 0.4 for market, 0.3 for artist, 0.2 for popularity, and 0.1 for speed.

In the following table, we compare the average figures of success signals of all artworks in the gallery with those of artworks in the selections by curators and artists.

market artist popularity speed TokenRank
gallery 0.694 0.509 0.556 0.207 0.562
curator 0.782 0.648 0.703 0.331 0.681
artist 0.821 0.669 0.781 0.461 0.731

It turns out that:

  1. artworks selected by curators and artists are significantly more successful than the average artwork in the gallery;
  2. however, the pieces selected by artists are significantly more successful than those selected by curators.

Assuming that all actors involved in this evaluation made their selection based only on the inherent quality of the artworks and regardless of their commercial success, we conclude that, for the dataset at hand, there exists a significant overlapping between prestige and success at the level of artworks. In other terms, quality art, as identified by art experts, is not ignored by art collectors and investors and makes its way through the market. However, the choices made by curators were much less success-oriented than those made by artists, and this highlights the different roles of curators (art experts, in principle independent from market) and artists (art makers, typically also related to market and commercial success).

It is worth noticing that we are not claiming that prestige and success match perfectly. Indeed, 32% of the artworks selected by curators were unsold at the time of selection (as a reference, the share of unsold gallery items at that time was 60%). On the other hand, only 3 artworks in the top-10 ranking according to TokenRank metric have also been selected by curators: Latent Space of Landscape Paintings #1, AI Generated Landscape Painting #4, and AI Generated Landscape #6, all created by Robbie Barrat.


In his recent book The Formula (Barabasi 2018), Barabasi draws an interesting parallel between the concepts of performance and success. While performance is an internal variable that depends on how we played the game, success is an external factor that depends on the recognition we receive from others for our performance.

Your success isn’t about you and your performance. It’s about us and how we perceive your performance. Albert-Laszlo Barabasi

In some contexts, for example in sport, the performance of an athlete is easily measurable and comparable with that of other athletes. In these cases, performance and success are strongly correlated. In other scenarios, such as art or cooking, the intrinsic quality of the work is difficult to assess. In these cases, performance is only one of the ingredients of success. Our position within the network in which we work is what determines the rest of the success, according to the findings of Barabási and co-authors. In art, for example, this network, often invisible, involves artists, collectors, galleries, curators, agents, art historians, auction houses (Fraiberger et al. 2018).

Performance drives success, but when performance can’t be measured, network drives success. Albert-Laszlo Barabasi

In this work we tested the association between performance (we call it prestige) and success in the very recent art movement known as crypto art. We invited art experts to select meaningful artworks from SuperRare gallery, the major marketplace for crypto art at the moment. Then we correlated the selected artworks with signals of success of the artworks in the gallery. The outcome was somewhat surprising: curators tend to identify themselves with the observer and in doing so they anticipate the likes of the mass, as artworks praised by them are also appreciated by the market. Finding a balance between popularity and artistic talent is something curators are naturally attracted to. Moreover, we observed that the role of art experts and art makers are different: the former are attracted by the political and reflexive aspects of art and the latter are allured by its emotional and technological facets. It would be interesting to investigate if these findings are confirmed or refuted in the traditional art market.


We thank all curators and artists that participated in this research as well as Serena Tabacchi for putting us in contact with some of the curators.


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———. 2018. “What Is Cryptoart?”

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