A Survey on Decentralized Metaverse Using Blockchain and Web 3.0 Technologies, Applications, and More
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This survey delves into the convergence of blockchain, Web 3.0 technologies, and the decentralized metaverse, analyzing their combined effects on virtual experiences. The study meticulously examines the decentralized metaverse’s architecture, intrinsic properties, and transformative potential. Central to our analysis is the role of blockchain technology in addressing scalability issues and presenting practical applications in virtual real estate, gaming, and social interactions. Furthermore, we explore consensus mechanisms such as Proof of Work (PoW) and Proof of Stake (PoS), emphasizing their significance in the decentralized framework. The survey also investigates governance models and exceptionally Decentralized Autonomous Organizations (DAOs) and identifies associated challenges, including data security threats and possible mitigation strategies. By incorporating case studies on platforms like Decentraland, Vault Hill, and The Sandbox, we illustrate real-world implementations and emerging trends within the decentralized metaverse. This research highlights the profound implications of decentralized technologies on digital interactions, economies, and governance, marking a pivotal shift towards the Web 3.0 era. It underscores the potential for these technologies to redefine ownership, identity, and social engagement in virtual environments. Moreover, the paper outlines future research opportunities, encouraging further exploration into the integration and advancement of decentralized systems within the metaverse. The survey provides a comprehensive overview of the decentralized metaverse, supported by blockchain and Web 3.0 technologies. It offers valuable insights into the challenges and opportunities within this rapidly evolving domain, paving the way for innovative applications and research directions to shape the future of digital interaction and governance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it