Trend Analysis of Decentralized Autonomous Organization Using Big Data Analytics

Inf. Comput. Pub Date : 2023-06-09 DOI:10.3390/info14060326
H. Park, Ivan Ureta, Boyoung Kim
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引用次数: 2

Abstract

Decentralized Autonomous Organizations (DAOs) have gained widespread attention in academia and industry as potential future models for decentralized governance and organization. In order to understand the trends and future potential of this rapidly growing technology, it is crucial to conduct research in the field. This research aims at a data-driven approach for the objective content analysis of big data related to DAOs, using text mining and Latent Dirichlet Allocation (LDA)-based topic modeling. The study analyzed tweets with the hashtag #DAO and all Reddit data with “DAO”. The results were from the identification of the top 100 frequently appearing keywords, as well as the top 20 keywords with high network centrality, and key topics related to finance, gaming, and fundraising, from both Twitter and Reddit. The analysis revealed twelve topics from Twitter and eight topics from Reddit, with the term “community” frequently appearing across many of these topics. The findings provide valuable insights into the current trend and future potential of DAOs, and should be used by researchers to guide further research in the field and by decision makers to explore innovative ways to govern the organizations.
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利用大数据分析去中心化自治组织的趋势分析
去中心化自治组织(Decentralized Autonomous Organizations, dao)作为去中心化治理和组织的潜在未来模式,在学术界和工业界得到了广泛关注。为了了解这种快速发展的技术的趋势和未来潜力,在该领域进行研究是至关重要的。本研究旨在利用文本挖掘和基于潜在狄利克雷分配(Latent Dirichlet Allocation, LDA)的主题建模,为dao相关大数据的客观内容分析提供数据驱动方法。该研究分析了带有#DAO标签的推文和所有带有“DAO”的Reddit数据。结果是通过识别Twitter和Reddit上出现频率最高的100个关键词,以及网络中心度最高的20个关键词,以及与金融、游戏和筹款相关的关键话题。该分析揭示了推特上的12个话题和Reddit上的8个话题,其中“社区”一词经常出现在这些话题中。这些发现为dao的当前趋势和未来潜力提供了有价值的见解,应该被研究人员用来指导该领域的进一步研究,并被决策者用来探索治理组织的创新方法。
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