Trend Analysis of Decentralized Autonomous Organization Using Big Data Analytics
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 resear...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-06-01
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| Series: | Information |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2078-2489/14/6/326 |
| _version_ | 1797594222327496704 |
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| author | Hyejin Park Ivan Ureta Boyoung Kim |
| author_facet | Hyejin Park Ivan Ureta Boyoung Kim |
| author_sort | Hyejin Park |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-11T02:20:35Z |
| format | Article |
| id | doaj.art-a3487c40cb8d40aaada3b77c3ceccf5d |
| institution | Directory Open Access Journal |
| issn | 2078-2489 |
| language | English |
| last_indexed | 2024-03-11T02:20:35Z |
| publishDate | 2023-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Information |
| spelling | doaj.art-a3487c40cb8d40aaada3b77c3ceccf5d2023-11-18T10:54:33ZengMDPI AGInformation2078-24892023-06-0114632610.3390/info14060326Trend Analysis of Decentralized Autonomous Organization Using Big Data AnalyticsHyejin Park0Ivan Ureta1Boyoung Kim2Seoul Business School, aSSIST University, Seoul 03767, Republic of KoreaDepartment of Business Economics, Health and Social Care, The University of Applied Sciences and Arts of Southern Switzerland, 6928 Manno, SwitzerlandSeoul Business School, aSSIST University, Seoul 03767, Republic of KoreaDecentralized 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.https://www.mdpi.com/2078-2489/14/6/326decentralized autonomous organization (DAO)blockchainbig data analyticstext miningnetwork analysis |
| spellingShingle | Hyejin Park Ivan Ureta Boyoung Kim Trend Analysis of Decentralized Autonomous Organization Using Big Data Analytics Information decentralized autonomous organization (DAO) blockchain big data analytics text mining network analysis |
| title | Trend Analysis of Decentralized Autonomous Organization Using Big Data Analytics |
| title_full | Trend Analysis of Decentralized Autonomous Organization Using Big Data Analytics |
| title_fullStr | Trend Analysis of Decentralized Autonomous Organization Using Big Data Analytics |
| title_full_unstemmed | Trend Analysis of Decentralized Autonomous Organization Using Big Data Analytics |
| title_short | Trend Analysis of Decentralized Autonomous Organization Using Big Data Analytics |
| title_sort | trend analysis of decentralized autonomous organization using big data analytics |
| topic | decentralized autonomous organization (DAO) blockchain big data analytics text mining network analysis |
| url | https://www.mdpi.com/2078-2489/14/6/326 |
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