MiningVis: Visual Analytics of the Bitcoin Mining Economy
Natkamon Tovanich, Nicolas Soulié, Nicolas Heulot, Petra Isenberg
摘要
Fig. 1. A screenshot of the MiningVis tool. (V1) The time filter view allows analysts to select a time interval of interest. (V2) The mining distribution view shows the evolution of the mining pools as a ribbon chart. (V3) The mining pool details view shows mining power and pool characteristics for each mining pool in a compound chart. (V4) The Bitcoin statistics view shows Bitcoin network statistics as a list of area charts (see Fig. 4). (V5) The Bitcoin news view displays a swarm plot of the news distribution over time. (V6) The cross pooling view represents the total reward of cross pooling miners in mining pools at the time interval on a chord diagram.
Abstract-We present a visual analytics tool, MiningVis, to explore the long-term historical evolution and dynamics of the Bitcoin mining ecosystem. Bitcoin is a cryptocurrency that attracts much attention but remains difficult to understand. Particularly important to the success, stability, and security of Bitcoin is a component of the system called "mining." Miners are responsible for validating transactions and are incentivized to participate by the promise of a monetary reward. Mining pools have emerged as collectives of miners that ensure a more stable and predictable income. MiningVis aims to help analysts understand the evolution and dynamics of the Bitcoin mining ecosystem, including mining market statistics, multi-measure mining pool rankings, and pool hopping behavior. Each of these features can be compared to external data concerning pool characteristics and Bitcoin news. In order to assess the value of MiningVis, we conducted online interviews and insight-based user studies with Bitcoin miners. We describe research questions tackled and insights made by our participants and illustrate practical implications for visual analytics systems for Bitcoin mining.
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
引用它的顶会 Paper2
- In Defence of Visual Analytics Systems: Replies to CriticsAoyu Wu, Dazhen Deng, Furui Cheng, Yingcai Wu 等IEEE VIS 2022 · 被引用 30 次
- NFTDisk: Visual Detection of Wash Trading in NFT MarketsXiaolin Wen, Yong Wang, Xuanwu Yue, Feida Zhu 等CHI 2023 · 被引用 28 次
相关 Paper
- LargeNetVis: Visual Exploration of Large Temporal Networks Based on Community TaxonomiesClaudio D. G. Linhares, Jean R. Ponciano, Diogenes S. Pedro, Luis E. C. Rocha 等IEEE VIS 2022 · 被引用 11 次
- BiaSeer: A Visual Analytics System for Identifying and Understanding Media BiasGuozheng Li, Shiyu Han, Jihe Wu, Jiale Hu 等CSCW 2025 · 被引用 2 次
- Characterizing Ethereum's Mining Power Decentralization at a Deeper LevelLiyi Zeng, Yang Chen, Shuo Chen, Xian Zhang 等INFOCOM 2021 · 被引用 14 次
- Visual Extraction of Interaction Patterns Guided by Hierarchical Clustering and Process MiningPeilin Yu, Aida Nordman, Takanori Fujiwara, Marta Koc-Januchta 等IEEE VIS 2025 · 被引用 2 次
- FairRankVis: A Visual Analytics Framework for Exploring Algorithmic Fairness in Graph Mining ModelsTiankai Xie, Yuxin Ma, Jian Kang, Hanghang Tong 等IEEE VIS 2021 · 被引用 30 次
