Datasets:
MLNTeam-Unical
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Update README.md
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README.md
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## Dataset summary
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The *NFT-70M_transactions* dataset is the largest and most up-to-date collection of Non-Fungible Tokens (NFT) transactions between 2021 and 2023 sourced from [OpenSea](https://opensea.io), the leading trading platform in the Web3 ecosystem.
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With more than 70M transactions enriched with metadata, this dataset
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Besides, the availability of textual descriptions and
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This dataset can serve as a benchmark for various innovative and impactful tasks within the crypto landscape, such as projecting NFT prices or detecting fraudolent and wash trading activities.
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Furthermore, the multimodal nature of the dataset fosters the development of classification models, as well as textual and visual generative models.
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## Data anonymization
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We point out that the collected NFT transactions and metadata from OpenSea are publicly distributed on blockchain.
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In this respect, we carried out three actions:
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- Values of all variables describing non-sensitive information were kept in their original form;
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- Values of all variables describing sensitive information were anonymized, in a one-way, non-revertible mode;
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- URLs of image and text data (i.e., NFT images and their descriptions) were replaced by identifiers to numerical vectors that represent an encrypted representation (i.e., embeddings) of the image/text contents obtained via neural network models.
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Such embeddings are eventually provided in place of their original
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## Data Fields
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## Dataset summary
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The *NFT-70M_transactions* dataset is the largest and most up-to-date collection of Non-Fungible Tokens (NFT) transactions between 2021 and 2023 sourced from [OpenSea](https://opensea.io), the leading trading platform in the Web3 ecosystem.
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With more than 70M transactions enriched with metadata, this dataset is conceived to support a wide range of tasks, ranging from sequential and transactional data processing/analysis to graph-based modeling of the complex relationships between traders.
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Besides, the availability of textual descriptions and multimedia resources, further amplifies the modeling capabilities and usage opportunities of this dataset, making it a unique and compehrensive multimodal source of information for delving into the NFT landscape.
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This dataset can serve as a benchmark for various innovative and impactful tasks within the crypto landscape, such as projecting NFT prices or detecting fraudolent and wash trading activities.
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Furthermore, the multimodal nature of the dataset fosters the development of classification models, as well as textual and visual generative models.
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## Data anonymization
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We point out that the collected NFT transactions and metadata from OpenSea are publicly distributed on blockchain.
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For our purposes of re-distribution, we are also committed to ensure non-disclosure of information that might lead to identifying the NFT creators, in order to be compliant with privacy-preserving requirements and to avoid violation of data protection regulations and of property rights.
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In this respect, we carried out three actions:
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- Values of all variables describing non-sensitive information were kept in their original form;
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- Values of all variables describing sensitive information were anonymized, in a one-way, non-revertible mode;
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- URLs of image and text data (i.e., NFT images and their descriptions) were replaced by identifiers to numerical vectors that represent an encrypted representation (i.e., embeddings) of the image/text contents obtained via neural network models.
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Such embeddings are eventually provided in place of their original image and text data, and can be found in the [**NFT-70M_image**](https://huggingface.co/datasets/MLNTeam-Unical/NFT-70M_image) and [**NFT-70M_text**](https://huggingface.co/datasets/MLNTeam-Unical/NFT-70M_text) supplementary datasets, respectively.
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## Data Fields
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