Metaverse, underpinned by blockchain infrastructure and cryptocurrency-based economies, represents a decentralized digital space where assets, identities and interactions are recorded. While commercial interactions between buyers and sellers are often highlighted, the actual functioning of Metaverses requires diverse participant roles operating behind the scenes. Some participants engage in unethical or underground digital activities that impact ecosystem integrity and fairness. Intellectual capital (IC) offers a comprehensive lens to describe the humans, relationships and structural assets that sustain these ecosystems. Exploring undercover role cooperations from an IC perspective is crucial for the proper regulation and governance of Metaverses.
This study constructs a theoretical framework of IC in Metaverses to guide the methodological design. We examine two prevalent Metaverse scenarios, GameFi and GambleFi, by conducting quantitative analysis on cryptocurrency transaction data, which serves as an integral structural capital of blockchain-based Metaverses. Specifically, we introduce a Graph Neural Network-based role discovery framework based on a time-sequenced transaction network to discover critical and behind-the-scene roles.
We identified distinct undercover roles across two scenarios: Profiteers, Laborers, Funding Allocators and Guild Managers in Play-to-Earn Games; Casino Stakeholders, Proxy-hosted Agents, Airdrop Recipients, Listing Agents and Arbitrageurs in Ethereum-based casinos. Roles as implicit human capital, and their cooperation as relational capital, are crucial for ecosystem functionality, yet also introduce labor exploitation, platform capitalism, market manipulation and ethical concerns.
Our findings enrich the theoretical landscape of IC and digital labor in Metaverses. They also offer actionable insights for regulators and platform developers to promote transparency, fairness and sustainability in virtual ecosystems.
