论文标题
AI方面的区块链：Twitter数据上的主题分析区块链安全性
AI Ethics on Blockchain: Topic Analysis on Twitter Data for Blockchain Security
论文作者
论文摘要
区块链使用分布式网络授权计算机系统更安全。但是，当前的区块链设计遇到了交易订购方面的公平问题。矿工能够重新订购交易以生成利润，即所谓的矿工可提取价值（MEV）。现有的研究将MEV视为严重的安全问题，并提出了包括突出的FlashBot的潜在解决方案。但是，以前的研究主要分析了区块链数据，这可能无法捕获MEV在更广泛的AI社会中的影响。因此，在这项研究中，我们应用了自然语言处理（NLP）方法来全面分析MEV推文中的主题。我们通过#MEV和#FlashBots主题标签收集了20000多条推文，并分析了它们的主题。我们的结果表明，这些推文讨论了道德关注的深刻主题，包括安全，公平，情感情感以及对MEV解决方案的渴望。我们还确定了区块链和社交媒体平台上MEV活动的共同动作。我们的研究在区块链安全，MEV解决方案和AI伦理的界面上有助于文献。
Blockchain has empowered computer systems to be more secure using a distributed network. However, the current blockchain design suffers from fairness issues in transaction ordering. Miners are able to reorder transactions to generate profits, the so-called miner extractable value (MEV). Existing research recognizes MEV as a severe security issue and proposes potential solutions, including prominent Flashbots. However, previous studies have mostly analyzed blockchain data, which might not capture the impacts of MEV in a much broader AI society. Thus, in this research, we applied natural language processing (NLP) methods to comprehensively analyze topics in tweets on MEV. We collected more than 20000 tweets with #MEV and #Flashbots hashtags and analyzed their topics. Our results show that the tweets discussed profound topics of ethical concern, including security, equity, emotional sentiments, and the desire for solutions to MEV. We also identify the co-movements of MEV activities on blockchain and social media platforms. Our study contributes to the literature at the interface of blockchain security, MEV solutions, and AI ethics.
