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 nft market


A Recommender System for NFT Collectibles with Item Feature

Choi, Minjoo, Kim, Seonmi, Kim, Yejin, Lee, Youngbin, Hong, Joohwan, Lee, Yongjae

arXiv.org Artificial Intelligence

Recommender systems have been actively studied and applied in various domains to deal with information overload. Although there are numerous studies on recommender systems for movies, music, and e-commerce, comparatively less attention has been paid to the recommender system for NFTs despite the continuous growth of the NFT market. This paper presents a recommender system for NFTs that utilizes a variety of data sources, from NFT transaction records to external item features, to generate precise recommendations that cater to individual preferences. We develop a data-efficient graph-based recommender system to efficiently capture the complex relationship between each item and users and generate node(item) embeddings which incorporate both node feature information and graph structure. Furthermore, we exploit inputs beyond user-item interactions, such as image feature, text feature, and price feature. Numerical experiments verify the performance of the graph-based recommender system improves significantly after utilizing all types of item features as side information, thereby outperforming all other baselines.


NFTs were meant to change everything – what happened?

The Guardian

A funny thing happened in Hong Kong earlier this month. Well, funny unless you were there. The annual ApeFest, where collectors of Bored Ape NFTs (remember them?) took place in Hong Kong (for the uninitiated, NFTs, or non-fungible tokens, can be linked to products like digital artworks and traded for cryptocurrencies on the open market). Nouveau-riche investors who got rich off the back of the revolutionary technology and investment products came together to party. A number of them reported suffering from "eye burn, extreme pain and impaired vision after attending one of its events, which was lit by UV lights".


What Determines the Price of NFTs?

Ziemke, Vivian, Estermann, Benjamin, Wattenhofer, Roger, Wang, Ye

arXiv.org Artificial Intelligence

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.


Abnormal Trading Detection in the NFT Market

Song, Mingxiao, Liu, Yunsong, Shah, Agam, Chava, Sudheer

arXiv.org Artificial Intelligence

The Non-Fungible-Token (NFT) market has experienced explosive growth in recent years. According to DappRadar, the total transaction volume on OpenSea, the largest NFT marketplace, reached 34.7 billion dollars in February 2023. However, the NFT market is mostly unregulated and there are significant concerns about money laundering, fraud and wash trading. The lack of industry-wide regulations, and the fact that amateur traders and retail investors comprise a significant fraction of the NFT market, make this market particularly vulnerable to fraudulent activities. Therefore it is essential to investigate and highlight the relevant risks involved in NFT trading. In this paper, we attempted to uncover common fraudulent behaviors such as wash trading that could mislead other traders. Using market data, we designed quantitative features from the network, monetary, and temporal perspectives that were fed into K-means clustering unsupervised learning algorithm to sort traders into groups. Lastly, we discussed the clustering results' significance and how regulations can reduce undesired behaviors. Our work can potentially help regulators narrow down their search space for bad actors in the market as well as provide insights for amateur traders to protect themselves from unforeseen frauds.


Are The Metaverse And Web3 Still Relevant?

#artificialintelligence

Generative AI, ChatGPT, Dall-E - it seems everyone's so excited about AI at the moment that they've forgotten all about the hot technology trends of just a short while back. Are The Metaverse And Web3 Still Relevant? This is the nature of the "hype cycle" that those of us who follow the latest developments in technology have become very accustomed to. New ideas get a lot of attention – not always of the right sort – then the excitement dies off when something even newer emerges. But does that mean that they're dead and forgotten?


Exploring Gender and Race Biases in the NFT Market

Zhong, Howard, Hamilton, Mark

arXiv.org Artificial Intelligence

Non-Fungible Tokens (NFTs) are non-interchangeable assets, usually digital art, which are stored on the blockchain. Preliminary studies find that female and darker-skinned NFTs are valued less than their male and lighter-skinned counterparts. However, these studies analyze only the CryptoPunks collection. We test the statistical significance of race and gender biases in the prices of CryptoPunks and present the first study of gender bias in the broader NFT market. We find evidence of racial bias but not gender bias. Our work also introduces a dataset of gender-labeled NFT collections to advance the broader study of social equity in this emerging market.


How will AI reshape the NFT industry?

#artificialintelligence

Technological advancement coupled with Artificial intelligence (AI) has taken over industries in the 21st century. For example, non-Fungible Tokens (NFTs) have exploded in popularity in recent years as a means of buying, selling, and trading unique digital assets such as artwork, music, and videos. As NFTs continue to gain in popularity, the incorporation of Artificial Intelligence is reshaping the NFT industry. Artificial Intelligence technology enables artists, collectors, and investors to generate, authenticate, and monetize non-fungible tokens in novel ways. The process of creating and validating NFTs becomes more rapid, efficient, and secure with Artificial Intelligence.


Will the next STAR WARS originate from an NFT?

#artificialintelligence

Star Wars is one of the most popular sci-fi brands in history and has inspired and captivated generations of fans. Can this feat be repeated? I believe the booming Web 3.0 culture, supported by NFTs can be a launchpad for a new mega-hit cultural sci-fi brand. NFT (Non-Fungible Token) is a new world that lots of people are not familiar with. Imagine the Internet in the early 1990s.