Projects per year
Abstract
Supporting Non-Fungible Token (NFT) Software Development enables the creation and sale of blockchain-based NFTs backed by unique digital or physical assets. Its value classification is important to justify investment in software development. This study surveys the rapid increase in NFT popularity and proposes a methodology to assess the valuation of an NFT and be able to predict the ultimate success of an NFT. The main influential factors identified in the study are the community and scarcity, our result confirms these two main factors that can affect an NFT's valuation, and this poster paper will look in depth at the correlation between the factors and the value of the NFT and provides the future direction of research. © 2022 IEEE.
Original language | English |
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Title of host publication | Proceedings - 2022 29th Asia-Pacific Software Engineering Conference |
Subtitle of host publication | APSEC 2022 |
Publisher | IEEE |
Pages | 564-565 |
ISBN (Electronic) | 9781665455374 |
ISBN (Print) | 978-1-6654-5538-1 |
DOIs | |
Publication status | Published - Dec 2022 |
Event | 29th Asia-Pacific Software Engineering Conference (APSEC 2022) - Virtual, Japan Duration: 6 Dec 2022 → 9 Dec 2022 |
Publication series
Name | Proceedings - Asia-Pacific Software Engineering Conference, APSEC |
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ISSN (Print) | 1530-1362 |
ISSN (Electronic) | 2640-0715 |
Conference
Conference | 29th Asia-Pacific Software Engineering Conference (APSEC 2022) |
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Country/Territory | Japan |
Period | 6/12/22 → 9/12/22 |
Funding
This work is supported in part by the General Research Fund of the Research Grants Council of Hong Kong (No. 11208017) and the research funds of City University of Hong Kong (No. 7005028 and 7005217), and the Research Support Fund by Intel (No. 9220097), and funding supports from other industry research partners.
Research Keywords
- Blockchain Software
- Cryptocurrency
- Digital Asset
- NFT Valuation
Fingerprint
Dive into the research topics of 'On the Scrutinization of the NFT Valuation Factors'. Together they form a unique fingerprint.Projects
- 2 Finished
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DON: Deep-learning based Software Engineering for Practical Software Analytics
Keung, J. W. (Principal Investigator / Project Coordinator)
1/11/18 → 20/09/23
Project: Research
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GRF: A Software Analytics Framework using Deep Learning on Generalized Data Representations
Keung, J. W. (Principal Investigator / Project Coordinator)
1/09/17 → 25/02/21
Project: Research