Visualizing NFT Ethics: A Case Study on CryptoPunks
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Project Summary:
As a blockchain-based application, Non-Fungible Token (NFT) has received worldwide attention over the past few years. Digital artwork is the main form of NFT that can be stored on different blockchains. Although the NFT market is rapidly developing, we observed potential ethical and racial fairness issues in the design of NFT artworks due to a lack of ethical guidelines or censorship. Therefore, we investigated CryptoPunks, the most famous collection in the NFT market, to explore and visualize its potential ethical issues. We explored the ethical issues from three aspects: design, trading transactions, and related topics on Twitter. We scraped data from Twitter and Dune Analytics using python libraries, Twitter crawler, and sentiment analysis tools. Our five visualizations implied that 1.6 times more male punks were created in the initial design process than the female ones. And the male ones have a higher average selling price than females; lighter-skinned punks tend to sell for higher prices. The results of our study and visualizations provide a preliminary exploration of CryptoPunks and further inspire future ethical-related investigation and research in the NFT domain.
Yufan Zhang is a senior student at Duke Kunshan University (DKU), where he is pursuing in a degree in Data Science (B.S.). He is also a member of the Inaugural E-Board, SciEcon CIC, where he serves as the Chair of Creativity and Innovation. He has a solid knowledge foundation of Data Science, Computer Science, and Blockchain Technology. He has great enthusiasm for applying computational strategies to generate innovation and advance society.
Yufan has participated in several interdisciplinary research projects on computer vision, computational biology, and blockchain-related topics like non-fungible token. Supervised by Prof. Peng Sun, he developed a novel GAN-based model for few-shot stylized multilingual font generation. Supervised by Prof. Huansheng Cao and Prof. Gaoyang Li, he proposed a novel Graph Neural Network (GNN) based model for predicting catalytic turnover numbers in Escherichia coli. He is now working on a blockchain-related research project supervised by Prof. Luyao Zhang and Prof. Xin Tong, on ethical issues in NFT design and marketplace. He also does not waste any chance to learn new skills, practice the newly-learning skills, and propose new ideas for exploratory research.
Zhichao Chen
Zichao Chen’s research interests are the development of the NFT marketplace and portfolio optimization in the cryptocurrency market. He is currently the Chair of SciEcon Research, before serving this position, he used to be the team leader of SciEcon NFT Lab and Lab Incubator Co-chair. He has also done some research in the NFT and Cryptocurrency field, one of the articles has been published on Medium and the others are being prepared to submit to world-leading conferences. Besides his experience in SciEcon, he is also a senior student majoring in Data Science at Duke Kunshan University. He is proficient in data analytics, mathematical modeling, and statistical principles. Zichao Chen also has strong practical application and learning abilities. He has working experience as Data Engineer in the world’s second-biggest short video platform Kuaishou (Kwai).
Creative Commons Attribution 4.0 International License (CC-BY 4.0)
