基于NFT转移网络中的集群聚合的核心-外围结构分析
Zijuan Chen1, Jianyong Yu1, Yulong Wang1
1School of Computer Science and Engineering, Hunan University of Science and Technology, Xiangtan 411100, China.
Entropy (Basel, Switzerland)
|April 26, 2025
概括
研究人员分析了非真菌代币 (NFT) 传输网络,使用贝叶斯式和随机区块模型识别核心节点. 他们的新方法提高了6-10%的结构表现,为NFT市场提供了洞察力.
科学领域:
- 区块链技术 区块链技术
- 网络科学 网络科学
- 数字资产数字资产
背景情况:
- 非可真菌代币 (NFT) 是以太坊等区块链平台上的一个新的数字资产类别.
- NFT转移网络显示复杂的核心-外围结构,基于分区方法的变化.
- 了解这些网络结构对于分析NFT市场至关重要.
研究的目的:
- 开发一种强大的方法来描述NFT转移网络中的核心-外围结构.
- 提高识别的网络结构的准确性和代表性.
- 为进一步的NFT市场分析提供理论基础.
主要方法:
- 提出了基于贝叶斯和随机区块模型 (SBM) 的方法,用于核心-外围结构的表征.
- 整合了先前的知识,以提高SBMs的合适性.
- 引入了一个局部加权的核心-外围结构聚合 (LWCSA) 方案,使用最小描述长度 (MDL) 原则.
主要成果:
- 确定核心节点作为NFT传输网络中总节点的一小部分 (2.3-5%).
- 与基线方法相比,实现了6-10%的正常化相互信息 (NMI) 指数的改善.
- 证明了提升的结构表示和提议方法的准确性.
结论:
- 开发的方法准确地描述了NFT网络结构,揭示了独特的核心-外围组织.
- 这些发现为NFT市场的动态提供了有价值的见解.
- 这项研究为数字资产领域的先进网络分析奠定了基础.
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