Modeling NFT Investor Behavior Using Belief Dissensus
Fernand Gobet and Percy Venegas
doi: 10.18278/jpcs.7.2.2
Fernand Gobet and Percy Venegas
doi: 10.18278/jpcs.7.2.2
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Abstract
Investment into non-fungible tokens (NFTs) has skyrocketed in 2021. Since NFTs are issued on blockchains, the underlying operation is that of a social computer—therefore, modeling social cognition in NFT markets becomes relevant. Market participants (collectors, speculators, and investors) may display different levels of expertise that serve as “social labels.” However, do users of NFT marketplaces care about price or community? Besides the operational consensus mechanism of the blockchain (which also provides the hard judiciary and settlement layers of the system), we must consider the soft consensus of the internet communities that drive their attention towards NFT marketplaces where the monetary assets are listed. In this research note, we propose an approach that offers a window on human cognition and collective intelligence, but that can inform the development of artificial systems that help develop policies to protect the public interest of investors.
Keywords: non-fungible tokens, NFTs, cryptomarkets, evolutionary algorithms, cognitive science
Investment into non-fungible tokens (NFTs) has skyrocketed in 2021. Since NFTs are issued on blockchains, the underlying operation is that of a social computer—therefore, modeling social cognition in NFT markets becomes relevant. Market participants (collectors, speculators, and investors) may display different levels of expertise that serve as “social labels.” However, do users of NFT marketplaces care about price or community? Besides the operational consensus mechanism of the blockchain (which also provides the hard judiciary and settlement layers of the system), we must consider the soft consensus of the internet communities that drive their attention towards NFT marketplaces where the monetary assets are listed. In this research note, we propose an approach that offers a window on human cognition and collective intelligence, but that can inform the development of artificial systems that help develop policies to protect the public interest of investors.
Keywords: non-fungible tokens, NFTs, cryptomarkets, evolutionary algorithms, cognitive science
