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Predictors of NFT Prices: An Automated Machine Learning Approach
Ilan Alon
, Vanessa P.G. Bretas
, Villi Katrih
Department of Economics and Business Administration
Research output
:
Contribution to journal
›
Article
›
peer-review
19
Scopus citations
Overview
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Dive into the research topics of 'Predictors of NFT Prices: An Automated Machine Learning Approach'. Together they form a unique fingerprint.
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Keyphrases
Machine Learning Approach
100%
AutoML
100%
Non-fungible Tokens
100%
Price Determinants
28%
Impact-based
14%
Twitter
14%
Discord
14%
Online Communities
14%
Social Community
14%
Incomplete Knowledge
14%
Comprehensive Dataset
14%
Pricing Model
14%
Blockchain
14%
Network Factors
14%
Digital Assets
14%
Smart Contract
14%
Computer Science
Machine Learning Approach
100%
Automated Machine Learning
100%
Non-Fungible Tokens
100%
Social Community
14%
Online Communities
14%
Blockchain
14%
Smart Contract
14%
Cryptographic Asset
14%
Economics, Econometrics and Finance
Machine Learning
100%
Price
100%
Pricing
50%
Ownership
25%
Social Sciences
Price
100%
Pricing
50%
Ownership
25%
Lack of Knowledge
25%
Online Communities
25%