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.
翻译：现有研究确认MEV是一个严重的安全问题,并提出了潜在的解决方案,包括著名的闪电机器人。然而,以往的研究大多对块链数据进行了分析,这些数据可能无法在更广泛的AI社会中捕捉MEV的影响。因此,在这项研究中,我们运用了自然语言处理方法全面分析MEV的推文主题。我们收集了2000多份Twitter,用“MEV”和“Flashbot”标签收集了2000多份Twitter,并分析了它们的主题。我们的研究结果显示,这些推文讨论了令人深为关注的伦理问题,包括安全、公平、情感情绪和对MEV的解决方案愿望。我们还确定了在块链和社会媒体平台上的MEV活动的共同动态。我们的研究为块链安全、MEV解决方案和AI道德的界面的文献作出了贡献。
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