Copycats vs. Original NFTs Detection: A Design Science Approach

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Abstract

Non-fungible tokens (NFTs) make trading digitalized artworks online possible and creates great opportunities in the artwork markets. Besides the extraordinary wealth it has created, the NFT trading market also brings many issues, such as intellectual property protection. Although there are a large number of transactions every day in the NFT market, there is no effective platform mechanism to avoid copycat behaviors. In this paper, we propose an NFT copycat detection and investigation framework. Besides, we propose to examine the effect of copycats on the price of the original NFTs. The proposed study contributes to the literature on NFT management and NFT copyright, and also helps NFT developers to protect their rights and benefits and helps NFT platforms to avoid potential legal issues.

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APA

Feiyu, E., Gao, H., & Chau, M. (2023). Copycats vs. Original NFTs Detection: A Design Science Approach. In Proceedings of the Annual Hawaii International Conference on System Sciences (Vol. 2023-January, pp. 4536–4542). IEEE Computer Society. https://doi.org/10.24251/hicss.2023.552

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