AI Ethics on Blockchain: Topic Analysis on Twitter Data for Blockchain Security
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Disclaimer: “This article is a final deliverable from Prof. Luyao Zhang's project entitled "Trust Mechanism Design: Blockchain for Social Good," supported by the 2022 Summer Research Scholarship (SRS) program at Duke Kunshan University. We give many thanks to DKU 2022 SRS program and SciEcon Insight editorial board.”
Part I: Research Summary
Information
“ AI Ethics on Blockchain: Topic Analysis on TwitterData for Blockchain Security” (Work in progress)
Blockchain has empowered computer system to be more secure by a distributed network. The traditional blockchain design fails to focus on transaction ordering. Instead, miners have complete control over transaction ordering. Maximal Extractable Value (MEV) is generated due to the delay between the transaction information transmitted to the network in the blockchain and the actual transaction information being packaged into the block. Potential solutions to be applied to democratize MEV. Previous literature focuses on blockchain security issues, democratization methods transition and MEV solutions. Besides these, scholars also focus on AI ethics by exploring and categorizing Twitter topics emerging in online social movements by implementing the Latent Dirichlet Allocation Model. They examined various influential topics in depth, including social justice, social movements, and emotional sentiment. However, literature on exploring and categorizing relations between online movements and reality MEV events has still been missing. In this paper, we answer three research questions: what are the connections between the Google trend and the Twitter volume of these two hashtags? What are the main keywords and topics being discussed in tweets with #MEV and #flashbots hashtags? What are the connections between the most frequent keywords in tweets with #MEV and #flashbots hashtags? By collecting data and applying quantitative methods, our study explores the mutual impact between MEV on/off-line events. It could guide future designs to AI ethics and blockchain security, which will bring world real impacts.
Part II: Related Research
1. Exploratory Research Articles Published on SciEcon Innovate
Smart Contract security and vulnerability detection: A fundamental framework for retrieving and execution
Yihang Fu is a junior undergraduate student at Duke Kunshan University majoring in Data Science. He received a quarter-admission scholarship and was supported by the 2022 Summer Research Scholarship. He is passionate about interdisciplinary Study and conducts pieces of research in different fields such as Blockchain security, natural language analysis, environment study, etc. He is keen on exploring and looks forward to converting the in-book knowledge to real-life applications. Yihang is also a member of SciEcon CIC.
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