We analyse the pattern of daily price of a collection of artistic non-fungible tokens, namely, the "Bored Ape Yacht Club" (BAYC) collectibles, over the first year of their life, from May 2021 to May 2022. Taking a time-series analysis approach, we consider the daily average price, and other variants of daily price index, derived from hedonic regression model. Aesthetic features of the collectibles do matter. At the same time, the price series emerge to be non-stationary, integrated of order 1, with their first difference exhibiting heteroscedasticity and autoregressive variance. Models of ARCH/GARCH class are appropriate to describe the dynamics. Though the price series of BAYC collectibles and their daily movements share many characteristics with the series of financial assets, they do not appear to be related to financial variables from both the crypto- and the real (i.e., not crypto) world.
Purpose: This case study explores the evolving landscape of digital art and non-fungible tokens (NFTs) through the journey of Niklas Elmehed, a renowned freelance artist responsible for the Nobel Laureate portraits. It delves into the challenges and opportunities presented by NFTs, touching upon topics such as data privacy, generative AI, and the changing nature of visual communication. Pedagogical Objective: The case aims to help learners understand the impact of NFTs on the art world, the cognitive theory of visual communication, and the influence of generative AI. It prompts critical thinking about the future of digital art, personal branding, and strategic choices for artists in the digital era. Case Positioning and Setting: This case is suitable for undergraduate and graduate courses in art, digital marketing, and entrepreneurship. It can be used to facilitate discussions on NFT adoption, the intersection of technology and art, and the implications for artists and collectors. The case protagonist is based in Stockholm, Sweden and the timeline is from 1997 to 2023.
<p><strong><a href="https://sites.google.com/99cryptowallet.com/boredapeyachtclubnft/">Bored Ape Yacht Club</a></strong> (BAYC) is the collection of 10,000 NFTs (non-fungible tokens) on the Ethereum (ETH) blockchain. These non-fungible tokens are graphical portrayals of cartoon-like apes that are unique by the metadata, which includes the clothes, backgrounds, earrings, eyes, and fur of the character. Metadata for NFTs is data about an illustration of the token that an NFT creator supplies. Introduced in 2021, the is similar to the artwork sold physically. But these artworks exist only virtually and are one of a kind as they remain on the blockchain.</p>
Vivian Ziemke, Benjamin Estermann, Roger Wattenhofer, Ye Wang
In the evolving landscape of digital art, Non-Fungible Tokens (NFTs) have emerged as a groundbreaking platform, bridging the realms of art and technology. NFTs serve as the foundational framework that has revolutionized the market for digital art, enabling artists to showcase and monetize their creations in unprecedented ways. NFTs combine metadata stored on the blockchain with off-chain data, such as images, to create a novel form of digital ownership. It is not fully understood how these factors come together to determine NFT prices. In this study, we analyze both on-chain and off-chain data of NFT collections trading on OpenSea to understand what influences NFT pricing. Our results show that while text and image data of the NFTs can be used to explain price variations within collections, the extracted features do not generalize to new, unseen collections. Furthermore, we find that an NFT collection's trading volume often relates to its online presence, like social media followers and website traffic.
Non-fungible tokens (NFTs) have recently gained widespread popularity as an alternative investment. However, the lack of assessment criteria has caused intense volatility in NFT marketplaces. Identifying attributes impacting the market performance of NFT collectibles is crucial but challenging due to the massive amount of heterogeneous and multi-modal data in NFT transactions, e.g., social media texts, numerical trading data, and images. To address this challenge, we introduce an interactive dual-centric visual analytics system, NFTeller, to facilitate usersâ analysis. First, we collaborate with five domain experts to distill static and dynamic impact attributes and collect relevant data. Next, we derive six analysis tasks and develop NFTeller to present the evolution of NFT transactions and correlate NFTsâ market performance with impact attributes. Notably, we create an augmented chord diagram with a radial stacked bar chart to explore intersections between NFT collection projects and whale accounts. Finally, we conduct three case studies and interview domain experts to evaluate the effectiveness and usability of this system. As such, we gain in-depth insights into assessing NFT collectibles and detecting opportune moments for investment.
The adoption of non-fungible tokens (NFTs) has revolutionized digital art transactions, providing artists with unprecedented opportunities to tokenize and monetize their generative creations, leading to increased scrutiny and demand within blockchain-oriented marketplaces. The pricing of NFT artworks, however, exhibits substantial variations within and across collections, influenced by various factors. This study aims to investigate the relationship between visual features and pricing, shedding light on the variations underlying the pricing of NFTs. First, measures of both computational aesthetics and visual complexity were applied to extract multi-faceted visual aesthetic features, encompassing aesthetic factors such as color and composition as well as complexity factors like entropy. Second, with extracted visual aesthetic features and preprocessed price data, the study proceeds to conduct correlation analysis within collections and statistical modeling across collections. Through these approaches, we reveal a moderate correlation between visual features and prices within collections, while also identifying different influential visual features across collections. The differential performance of price models highlights the distinctiveness and unique pricing characteristics of NFT collections.
D. C. Jain, Megh Dedhia, Jinay Parekh, Kiran Bhowmick
Non-Fungible Tokens (NFTs) have emerged as a popular form of digital asset ownership and trading on Web 3.0. In particular, generative NFT art collections such as Cryp-toPunks, Bored Ape Yacht Club, Mutant Ape Yacht Club, and others have seen significant hype and monetary value, with some individual NFTs selling for millions of dollars. With such high stakes involved, it is critical for NFT collectors and those interested in starting their own collections to have access to reliable and comprehensive data analysis tools that can help them make informed decisions. This research paper presents a data extraction and analysis tool for generative NFT art collections that aims to address this need. The tool leverages publicly available data from blockchain ledgers to scrape and extract information on various collections, including details such as ownership, transaction history, rarity, and more. The extracted data is then transformed from an unstructured to a structured format and analyzed using various statistical and machine-learning techniques to identify patterns, trends, and insights. Through the use of this tool, NFT collectors and individuals interested in starting their own collections can gain valuable insights into the performance and value of different generative NFT art collections over time. For example, the tool can help users identify which collections have experienced the highest growth in value, which NFTs within a collection are the most valuable, and which collections are most likely to increase in value in the future. Overall, this research paper presents a comprehensive data extraction and analysis tool for generative NFT art collections. By enabling users to conduct better research and make more informed decisions, the tool has the potential to increase the success and profitability of NFT collectors and those interested in starting their own collections in rapidly evolving NFT markets.
Abstract While most influential in art markets, the non-fungible token (NFT) phenomenon also has serious ramifications for museums and other cultural institutions. This chapter explores these applications to core nonprofit missions and activities, including audience development, fundraising, earned-income generation, acquisitions, and institutionsâ relationships with their communities. Any initiative involving NFTs at a museum is also an exercise in strategic planning. We develop a novel conceptual framework around mapping institutionsâ financial and philosophical priorities to guide strategic planning around NFTs. We present this framework through five case studies that range from existing museum projects around revenue generation, conservation, and endowment to two hypothetical scenarios around deaccessioning, restitution, and institutionsâ relationships with their audiences. Cultural institutions apart from museums may also find the framework valuable and worth incorporating into their strategic planning processes, as it can be tailored to an organizationâs individual priorities, artistic missions, and financial needs.
Benedetta Carraro, Alberto Sanna, Francesca Pola, Matteo Zardin
This article presents the NEFFIE (which stands for âNeuroaesthetic Photographyâ) project, a contemporary reinterpretation of Franco Vaccariâs iconic artwork, presented 50 years ago at the 1972 International Venice Art Biennale and entitled Exhibition in Real Time No. 4: Leave on the Walls a Photographic Trace of Your Fleeting Visit . Thanks to todayâs technological innovation, NEFFIE develops Vaccariâs idea from a more contemporary perspective. Vaccariâs original photo booth becomes a technologically revisited booth that uses an algorithm and wearable sensors to reshape the subjective emotional-cognitive responses derived from viewing particular images, thus generating the âcognitive photographâ or âCOFFIE metapictureâ. These metapictures are subsequently minted as NFTs (non-fungible tokens) objects and then displayed on a virtual wall, the âCOFFIE wallâ, generating what can be defined as a Virtual Exhibition in Real Time , a hypothetical contemporary re-actualization of Vaccariâs artistic proposition. The NEFFIE project could be considered a pervasive media art proposal capable of promoting social cohesion, by encouraging creative participation and co-creation. The project is being developed in Milan, thanks to a fruitful interdisciplinary collaboration between the Research Center in Advanced Technology in Health and Well-Being of San Raffaele Hospital, and ICONE, the European Research Center in History and Theory of the Image of Vita-Salute San Raffaele University. This multidisciplinary approach combines art-historical theoretical thinking with the world of technological innovation. In particular, the NEFFIE project integrates the visual and conceptual tools of photography with the methodologies and knowledge of biomedical engineering and computer science.
Seonmi Kim, Y. C. Lee, Yejin Kim, Joohwan Hong ¡ 5 authors
Recommender systems have become essential tools for enhancing user experiences across various domains. While extensive research has been conducted on recommender systems for movies, music, and e-commerce, the rapidly growing and economically significant Non-Fungible Token (NFT) market remains underexplored. The unique characteristics and increasing prominence of the NFT market highlight the importance of developing tailored recommender systems to cater to its specific needs and unlock its full potential. In this paper, we examine the distinctive characteristics of NFTs and propose the first recommender system specifically designed to address NFT market challenges. In specific, we develop a Multi-Attention Recommender System for NFTs (NFT-MARS) with three key characteristics: (1) graph attention to handle sparse user-item interactions, (2) multi-modal attention to incorporate feature preference of users, and (3) multi-task learning to consider the dual nature of NFTs as both artwork and financial assets. We demonstrate the effectiveness of NFT-MARS compared to various baseline models using the actual transaction data of NFTs collected directly from blockchain for four of the most popular NFT collections. The source code and data are available at https://anonymous.4open.science/r/RecSys2023-93ED.
This chapter examines characteristics of non-fungible tokens (NFTs) and factors of perceived consumer value that influence the intention to purchase NFT sports collectibles. It further offers recommendations through which NFT experiences can be enhanced for collectors. The role of NFT sports collectibles is introduced in the context of the internet of things and internet of value before defining NFT characteristics and consumer value factors relevant to this study. The respective conceptual model is then analyzed and discussed. The main findings explain that NFT characteristics including scarcity, uniqueness, aesthetics, and functional utility have no direct effect on the purchase intention for NFT sports collectibles. However, they have a significant and positive influence on the purchase intention when mediated through consumer values like the enjoyment of collecting NFTs, the creativity stimulated from assembling a digital collection, and the social relationships that can be fostered with other collectors.
Consumer Behavior in Brand Consumption and Identification
Clearly, digital technologies have been developed rapidly, and it affects art form significantly. For instance, visual works, where were displayed and sold in the art galleries have shifted into the blockchain networks nowadays. As a result, it makes NFT (Non-Fungible Token) becoming extremely popular, mainly in Generation-Z. This study aims to discuss how visual communication design students as a part of Gen-Z are introduced to the world of NFT as a visual archiving solution through the art history learning method in Bina Nusantara University. In addition, this study sees to what extent art history could be implied in the NFT art in order to attract Gen-Z to learn history and gaining analytical and critical ability. In order to design a historical NFT art, first, students should be able to understand the cultural concepts that exist in each particular era, from the mindset, characteristics, to the main essence of that period. From the analysis of previous artefacts and any great relics that were exist, students are capable to express their thoughts about the certain culture and providing conclusions from each era they adopt. Through this process, a historical NFT art that emphasize the origin meaning in the past and executed through visuals that tailored to the needs of Gen-Z would be successfully achieved. To sum up, this study found that even digital assets could not be separated from enculturation and history.
The integration of generative artificial intelligence (AI) tools in art and design has disrupted the traditional creative landscape, leading to debates on the legitimacy of AI-generated art and the emergence of new markets such as non-fungible tokens (NFTs). The US Copyright Officeâs February 21, 2023, ruling withdrawing copyright protection for AI-generated comic artwork, while protecting the accompanying text and arrangement, highlights the contested nature of AI art and suggests that significant human intervention in the creative process will be required for monetization. Whether considered content interpolation or content creation, AI generative content for the creation of art and design is here with human-AI collaboration. To explore the potential of AI tools in creative practice, this study introduced students in a digital art course to Craiyon and Midjourney generative AI tools, with DALL-E 2 selected as the primary tool due to its varied output. The students were tasked with selecting a preferred prompt from one tool and then reproducing the output from both tools. The results revealed significant variations in replicating the outputs of different AI tools and limited exploration of prompt engineering, leading to restrictions in the iterative process of artmaking. The students agreed that generative AI tools are not a substitute for human creativity and should be used for final projects. The study demonstrates the potential and limitations of integrating AI tools in art and design and suggests the need for further research in developing effective prompt engineering strategies.
Alicia Cork, Adam Joinson, Laura G. E. Smith, David A. Ellis ¡ 5 authors
Non-fungible tokens (NFTs) allow individuals to demonstrate ownership of digital and physical assets. NFTs are scarce, unique, and authentic; three properties known to be key for determining perceived value. Whilst previous research has primarily focused on NFTs as a source of economic value, here we assess the psychological motivations of collectors of digital fashion NFTs. Specifically, NTFs related to digital fashion are particularly relevant to HCI researchers as they sit at the intersection between business, culture, and self-expression. Here, we survey 19 users of a digital avatar fashion company, Genies, to understand the gratifications users derive from collecting digital NFT fashion. Results demonstrate that the primary motivations for collecting fashion NFTs are self-expression and utility and that motivations associated with value are secondary. We make design recommendations based on these results, indicating that developers should distinguish between expression-based motivations and value-based motivations.
The explosive growth of non-fungible tokens (NFTs) on Web3 has created a new frontier for digital art and collectibles, but also an emerging space for fraudulent activities. This study provides an in-depth analysis of NFT rug pulls, which are fraudulent schemes aimed at stealing investors' funds. Using data from 758 rug pulls across 10 NFT marketplaces, we examine the structural and behavioral properties of these schemes, identify the characteristics and motivations of rug-pullers, and classify NFT projects into groups based on creators' association with their accounts. Our findings reveal that repeated rug pulls account for a significant proportion of the rise in NFT-related cryptocurrency crimes, with one NFT collection attempting 37 rug pulls within three months. Additionally, we identify the largest group of creators influencing the majority of rug pulls, and demonstrate the connection between rug-pullers of different NFT projects through the use of the same wallets to store and move money. Our study contributes to the understanding of NFT market risks and provides insights for designing preventative strategies to mitigate future losses.
A generative adversarial network is a deep learning model, an unsupervised learning method. In computer vision, the generative adversarial network is a research direction with rapid development in recent years; Similarly, the rise of cryptocurrency Non-Fungible Tokens (NFT) in recent years has also attracted much attention to the field of art. As an "irreplaceable currency" NFT provides a more novel and convenient way for content creators and artists to create and increases the continuous income of original creators. At the same time, it has also attracted widespread attention to the financial field. Therefore, this paper is determined to combine the generative adversarial network of the production of NFT and discuss and analyze the autonomous computer generation of artworks. Firstly, this paper starts with the model's structure, the design of the objective function, Block chain technology, and Irreplaceable tokens encrypted using blockchain technology. Then, the image generated by the whole generative adversarial network and transformed into NFT works are described in detail. In addition, this paper briefly discusses the development ethics of human art and machine art and the prospects for its development trend.
Open access
Generative Adversarial Networks and Image Synthesis
Technology has become a fundamental part of our environment, yet the borders between the physical and virtual realms become even more blurred. The introduction of the Metaverse is one of the most recent and notable innovations. It, just as any other technological advances, adapts to evolution in user needs serving as a link between the real and digital realms. While people can buy goods and services with a certain currency in the physical realm, cryptocurrencies and non-fungible tokens (NFTs) are used for transactions in the Metaverse. NFT provides customers a certificate of ownership, which means that their virtual commodities or assets such as lands or objects cannot be replicated. They may also be used to represent social standing, just like tangible goods and services. It has become increasingly common to come across museums displaying artworks or artists who sell their artworks as Non-fungible tokens (NFTs) on digital platforms such as Rarible, Mintable or OpenSea. This research discusses the 3D printability of NFTs and proposes a framework in order to create a hybrid experience for 3D printed NFT artworks. The results have shown that 3D printing of NFTs provided users/customers a hybrid experience in both realms, maintaining the artworksâ uniqueness and rarity, proof of ownership, as well as physical copies in hand. Moreover, the artists who were afraid of publicly displaying their artworks for the concern of being copied have created 3D printable designs that enabled them to easily and safely promote their designs to the public.
The fervor for Non-Fungible Tokens (NFTs) attracted countless creators, leading to a Big Bang of digital assets driven by latent or explicit forms of inspiration, as in many creative processes. This work exploits Vision Transformers and graph-based modeling to delve into visual inspiration phenomena between NFTs over the years, i.e., the visual influence that can be detected whenever an NFT appears to be visually close to another that was published earlier in the market. Our goals include unveiling the main structural traits that shape visual inspiration networks, exploring the interrelation between visual inspiration and asset performances, investigating crypto influence on inspiration processes, and explaining the inspiration relationships among NFTs. Our findings unveil how the pervasiveness of inspiration led to a temporary saturation of the visual feature space, the impact of the dichotomy between inspiring and inspired NFTs on their financial performance, and an intrinsic self-regulatory mechanism between markets and inspiration waves. Our work can serve as a starting point for gaining a broader view of the evolution of Web3.
Non-Fungible Tokens (NFTs) are a type of digital asset that represents a proof of ownership over a particular digital item such as art, music, or real estate. Due to the non-fungible nature of NFTs, duplicate tokens should not possess the same value. However, with the surge of new blockchains and a massive influx of NFTs being created, a wealth of NFT data is being generated without a method of tracking similarity. This enables people to create almost identical NFTs by changing one pixel or one byte of data. Despite the similarity among NFTs, each NFT is assigned a completely different token ID. To address the NFT duplication issue, we developed a modular, easily-extendable, hardware-agnostic, cloud-centered NFT processing system that represents NFTs as vectors. We established a database containing a vector representation of the NFTs in accordance with the Ethereum Request for Comment 721 (ERC-721) token standards to initiate the process of aggregating NFT data from various blockchains. Finally, we developed an NFT visualization dashboard application with a user-friendly graphical user interface (GUI) to provide non-technical users access to the aggregated NFT data. The Universal NFT Vector Database is an off-chain framework for NFT data aggregation based on similarity, which provides an organized way to query and analyze NFT data that was previously unavailable through on-chain solutions.
The purpose of this study is to create Digital images in the experimental creation with the support from Artificial Intelligence (AI) that is used to assist in the creation of artwork with frameworks newly designed to reduce time of the creation of digital art works without the decrease of quality of the works but will lever the works without destroying the personalities of the artists and the styles of works. Concerning the contents of the works, Thai arts and culture are used as the contents of contemporary works so that people nowadays still recognize applied arts in new forms. Therefore, there is the cooperation between AI and the artist in the new form of Digital Image, which has been publicized in NFT11Non-fungible token (NFT) is a unique digital identify in a blockchain used to certify authenticity and ownership. In this case is digital art image type. [7](Non-fungible Token) art market in order to get feedback which will be applied for further development. From the creation of the work, it has been discovered that AI generated Art is faster and fits standards. However, there still are many arguments in several issues in the art field. Thus, I, as the Artist, have designed the Frameworks to correct such arguments until this work is accepted and auctioned in NFT market eventually.
Generative Adversarial Networks and Image Synthesis
<title>Abstract</title> In recent years, interest in Non Fungible Tokens (NFTs) has soared and the NFT market has experienced significant growth. Built upon blockchain technology, the tokens represent a unique offering, a rarity, due to its attributes of immutability, trust, transparency, auditability and anonymity. These unique tokens are highly appealing and sought after by investors and traders, since ownership rights, provenance and authenticity are publicly available. As a result, NFTs can be applied in a wide range of contexts and sectors. One such sector is in the digital art market, where sales of NFTs skyrocketed during 2021, thereby generating a multibillion dollar ecosystem. However, due to the fast-changing evolution of NFTs, the increase in demand for the tokens, high returns and lack of regulation, fraud has become commonplace and many security issues have arisen in the ecosystem. In this paper, we explore some of these security issues. Furthermore, by investigating Interplanetary File System (IPFS) and hashing techniques, namely cryptographic and perceptual image hashing, in more detail, proof of concept (PoC) models were built to aid in the identification and combat of NFT fraud.
Currently, the best known applications of blockchain technology are finance and art. In particular, the blockchain art market, born in early 2018 without fuss, went parabolic around 2021, also thanks to record-breaking sales of digital artworks associated with a Non-Fungible Token (NFT), mediated by the grand dames of auction houses Christieâs and Sothebyâs. In this contribution we merge art and finance on blockchain and explore the opportunity of buying blockchain art as a financial investment. While there exists a relatively large literature on traditional art as investment, the topic of investing in NFTs is still in its infancy. Thus, we provide methods (metrics) and tools (a Web app) to reason about opportunities, in terms of risks and returns, of investing in art on chain.
Three years after the sensational debut of non-fungible tokens (NFTs) on the art scene, it seems timely to reflect on their presumed revolutionary attributes. The speculative fascination at the beginning has gradually given way to mixed outcomes, with hardly predictable future directions. However, once recontextualized in the art ecosystem and its value chain, one may question the ability of NFT technology to lead to radical changes. Our main argument is that although they offer perspectives that are worth considering regarding contracts, authorsâ rights management, and provenance, blockchain-based technologies do not substantially modify the typical characteristics of the art world. Based on recent press articles and academic publications, we comment on the effects of this technology on producers (artistsâ creative process and career development), intermediaries (art market gatekeepers), and consumers (quest for authenticity, collecting habits, and museum intervention in the art market). Our main conclusions suggest that NFTs perpetuate oversupply and job precarity in cyberenvironments and reinforce existing purchasing behaviors driven by the quest for authenticity and conspicuous consumption. Our goal is to mitigate some statements found in the literature and the press, especially regarding the democratization of the art market, and to help art market stakeholders approach this technology most objectively.