Wallets' explorations across non-fungible token collections
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arXiv
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| Autores principales: | , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| Acceso en línea: | |
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| _version_ | 1866913199596503040 |
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| author | Jo, Seonbin Jung, Woo-Sung Kim, Hyunuk |
| author_facet | Jo, Seonbin Jung, Woo-Sung Kim, Hyunuk |
| contents | Non-fungible tokens (NFTs), which are immutable and transferable tokens on blockchain networks, have been used to certify the ownership of digital images often grouped in collections. Depending on individual interests, wallets explore and purchase NFTs in one or more image collections. Among many potential factors of shaping purchase trajectories, this paper specifically examines how visual similarities between collections affect wallets' explorations. Our model shows that wallets' explorations are not random but tend to favor collections having similar visual features to their previous purchases. The model also predicts the extent to which the next collection is close to the most recent collection of purchases with respect to visual features. These results are expected to enhance and support recommendation systems for the NFT market. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2401_10138 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Wallets' explorations across non-fungible token collections Jo, Seonbin Jung, Woo-Sung Kim, Hyunuk Physics and Society Non-fungible tokens (NFTs), which are immutable and transferable tokens on blockchain networks, have been used to certify the ownership of digital images often grouped in collections. Depending on individual interests, wallets explore and purchase NFTs in one or more image collections. Among many potential factors of shaping purchase trajectories, this paper specifically examines how visual similarities between collections affect wallets' explorations. Our model shows that wallets' explorations are not random but tend to favor collections having similar visual features to their previous purchases. The model also predicts the extent to which the next collection is close to the most recent collection of purchases with respect to visual features. These results are expected to enhance and support recommendation systems for the NFT market. |
| title | Wallets' explorations across non-fungible token collections |
| topic | Physics and Society |
| url | https://arxiv.org/abs/2401.10138 |