Exploring the data of blockchain-based metaverses

TL;DR

This paper analyzes the diverse data types in blockchain-based metaverses and introduces a machine learning tool for data collection and analysis, demonstrating its application in digital real estate trading.

Contribution

It presents a novel analysis tool leveraging machine learning to study heterogeneous metaverse data, including blockchain transactions and social media trends.

Findings

Effective data collection and analysis of metaverse transactions

Insights into digital parcel trading dynamics

Demonstrated utility of the analysis tool in real-world scenarios

Abstract

In recent years the concept of metaverse has evolved in the attempt of defining richer immersive and interactive environments supporting various types of virtual experiences and interactions among users. This has led to the emergence of various different metaverse platforms that utilize blockchain technology and non-fungible tokens (NFTs) to establish ownership of metaverse elements and attach features and information to it. This article will delve into the heterogeneity of the data involved in these metaverse platforms, as well as highlight some dynamics and features of them. Moreover, the paper introduces a metaverse analysis tool developed by the authors, which leverages machine learning techniques to collect and analyze daily data, including blockchain transactions, platform-specific metadata, and social media trends. Experimental results are reported are presented with a use-case scenario focused on the trading of digital parcels, commonly referred to as metaverse real estate.