Young Soon Jeong, Ji Eun Jeong, Chae Hyun Lee, Jong Woo Park
Purpose: Non-Fungible Token (NFT) ART, based on NFT technology, represents a novel form of art that has recently garnered significant attention in the art market. NFT technology enables the assertion of ownership over digital data, introducing the concept of ownership into the digital realm. As digital data gains ownership, NFT ART is anticipated to be positively viewed as an investment and expected to become more active due to the characteristics of this new technology. Therefore, this study aims to verify the influence of NFT ART characteristics on perceived value. This study contributes to extracting the distinctive characteristics of NFT ART compared to other forms of art and to understanding the perceived value of NFT ART among consumers with purchasing experience.Methods: This study applied structural equation modeling to explore the relationships among the variables using SPSS 26.0 and R program version 4.2.3. A total of 320 questionnaires were retrieved, all of which were adopted as valid analytical samples without missing values.Results: The findings indicate that the decentralization, transparency, and scarcity of NFT ART positively influence the perceived usefulness and enjoyment among consumers, while security does not have a significant impact. This suggests that higher levels of decentralization, transparency, and scarcity in NFT ART enhance perceived usefulness and enjoyment for consumers, significantly influencing the perceived value. Furthermore, it was confirmed that these characteristics are considered important values and perceptions from the consumer’s perspective.Conclusion: The research presents positive factors for the activating of purchases among consumers considering buying NFT ART. It emphasizes the necessity of benefits for all participants to activate the art market. Additionally, the perceived value provides crucial insights for inducing active purchasing behavior in the NFT ART market and serves as a foundational study for further research.
In metaverse, digital assets are essential to define identity, shape the virtual environment, and facilitate economic transactions. This study introduces a novel feature to the metaverse by capturing a fundamental aspect of individuals–their conversations–and transforming them into digital assets. It utilizes natural language processing and machine learning methods to extract a key sentence from user conversations and matches them with emojis that reflect their sentiments. The selected sentence, which encapsulates the essence of the user’s statements, is then transformed into digital art through a generative visual model. This digital artwork is transformed into a non-Fungible Token (NFT), becoming a valuable digital asset within the blockchain ecosystem that is ideal for integration into metaverse applications. Our aim is that the management of personality traits as digital assets will foster individual uniqueness, enrich user experiences, and facilitate more personalized services and interactions with both like-minded users and non-player characters, thereby enhancing the overall user journey.
Abstract In the modern world, the fashion industry is constantly evolving, and digital technologies are having an increasingly significant impact on its development. Therefore, the research relevance is determined by the need to explore the features of modern digital fashion concerning the commercial aspect, ethical issues and concept of sustainable fashion. This research aims to predict the prospects for the development of digital fashion in the fashion and design industry, and is based on the following methods: analytical, comparative, generalisation and systematisation methods. The study results showed that digital fashion is becoming increasingly popular among well-known brands, designers and fashion houses, while the commercial use of digital fashion is expanding thanks to the non-fungible token (NFT) platform and other digital tools. At the same time, the research also identifies ethical issues related to the protection of intellectual property in digital reality. Furthermore, the research analyses the segmentation of the digital fashion market and forecasts the development of this industry until 2030 and beyond. In terms of the relationship with the concept of sustainable fashion, it is found that digital fashion can contribute to sustainable development by reducing the use of physical resources and preserving the environment.
This article delves into the intersection of Non-Fungible Tokens (NFTs), the art world, and the instrumental role of social media in advancing the proliferation of digital collections. NFTs, unique digital assets built on blockchain technology, have sparked a revolution in art ownership, identity verification, and creative expression. Through comprehensive exploration of its significance, challenges, and opportunities, this study demonstrates how NFTs have democratized art ownership, provided global recognition to artists of diverse backgrounds, and simultaneously granted direct access to collectors. A significant driving force behind the success of this blockchain technology lies in its investment potential. Social media platforms have transformed into virtual galleries, effectively amplifying artists' voices, enhancing societal insights and cultural levels, and shedding light on the global visibility of NFT projects. Case studies of successful NFT collaborations underscore the coexistence between NFTs and social media, highlighting the potential of both mediums in shaping the future of art and creativity. While acknowledging concerns such as copyright issues and environmental impacts, this article underscores the need for responsible actions and ongoing research to ensure a sustainable and pervasive future for NFTs in the art world.
The non-fungible token (NFT) market has experienced significant growth in recent years. Similar to real estate and artwork, NFT is illiquid and it does not have a market price. Thus, there arises a need for a comprehensive scoring system to analyze the value of NFTs. Using a single score is often inadequate, as NFT value is influenced by numerous factors and is assessed based on personal objectives. Addressing the issue, this study explores critical factors influencing NFT value and develops three scores to rank NFTs including rarity, return on investment (ROI), and reputation score. The scores serve to evaluate both NFTs and NFT collections. (i) The rarity score evaluates the level of scarcity, and it applies to NFTs within a collection. (ii) The reputation score evaluates the interest of communities in NFT projects, considering the number of followers and the interaction rate; the score is for NFT collections. (iii) The ROI score assesses the profit generated by NFTs; it applies to both NFTs and NFT collections. Our empirical results show that a well-distributed rarity score of NFTs enhances their demand and profit; high-rarity NFTs are typically associated with a low number of sale transactions. NFT collections with high ROI and high reputation generally draw more attention and yield a positive return. In addition to the three scores, this paper presents a system to collect and process a huge amount of blockchain and social network data for NFT evaluation.
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.
<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 users’ 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 NFTs’ 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.
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.
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 Office’s 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 artworks’ 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.
<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 Christie’s and Sotheby’s. 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, authors’ 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 (artists’ 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.