NFTeller: Dual Centric Visual Analytics of NFT Transactions
dc.contributor.author
Cao, Yifan
dc.contributor.author
Yang, Xingxing
dc.contributor.author
Xia, Meng
dc.contributor.author
Liu, Hongkun
dc.contributor.author
Shigyo, Kento
dc.contributor.author
Wei, Zeng
dc.contributor.author
Cheng, Furui
dc.contributor.author
Wang, Yang
dc.contributor.author
Yu, Qianhang
dc.contributor.author
Qu, Huamin
dc.date.accessioned
2023-06-09T11:06:55Z
dc.date.available
2023-06-04T04:32:35Z
dc.date.available
2023-06-09T11:06:55Z
dc.date.issued
2023
dc.identifier.isbn
978-1-6654-7578-5
en_US
dc.identifier.isbn
978-1-6654-7579-2
en_US
dc.identifier.other
10.1109/BigComp57234.2023.00057
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/615052
dc.description.abstract
Non-fungible tokens (NFTs) can certify the authenticity and scarcity of digital assets on the blockchain. There is an urgent need to identify impact attributes from various potential factors and further evaluate NFT collectibles. Nevertheless, the task is challenging due to the massive amount of heterogeneous and multi-modal data (e.g., social media text, numerical transaction data, and images) in NFT transactions. To this end, we present an interactive visual analytics system, NFTeller, that provides a dual-centric perspective analysis of NFT transactions. The system i) summarizes the temporal evolution and correlation of transaction patterns and dynamic impact attributes of NFT collection projects; ii) presents an augmented chord diagram with a radial stacked bar chart for exploring the co-collected projects and co-occurring whale accounts. We derive in-depth insights from case studies on a real data set to evaluate the systems' effectiveness and usability.
en_US
dc.language.iso
en
en_US
dc.publisher
IEEE
en_US
dc.subject
Non-fungible tokens (NFTs)
en_US
dc.subject
Blockchain
en_US
dc.subject
Visual analytics
en_US
dc.title
NFTeller: Dual Centric Visual Analytics of NFT Transactions
en_US
dc.type
Conference Paper
dc.date.published
2023-03-20
ethz.book.title
2023 IEEE International Conference on Big Data and Smart Computing (BigComp)
en_US
ethz.pages.start
293
en_US
ethz.pages.end
294
en_US
ethz.event
IEEE International Conference on Big Data and Smart Computing (BigComp 2023)
en_US
ethz.event.location
Jeju, South Korea
en_US
ethz.event.date
February 13-16, 2023
en_US
ethz.identifier.wos
ethz.publication.place
Piscataway, NJ
en_US
ethz.publication.status
published
en_US
ethz.date.deposited
2023-06-04T04:32:38Z
ethz.source
WOS
ethz.eth
yes
en_US
ethz.availability
Metadata only
en_US
ethz.rosetta.installDate
2023-06-09T11:06:56Z
ethz.rosetta.lastUpdated
2023-06-09T11:06:56Z
ethz.rosetta.versionExported
true
ethz.COinS
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Conference Paper [35261]