Unveiling social aggregation in the Decentraland metaverse platform

Abstract

The advent of metaverse platforms has caused a revolution in the way people interact and engage with digital content creation and consumption. These platforms employ advanced technologies like blockchain and augmented reality to provide users with a fully decentralized environment. Among the metaverse platforms, Decentraland stands out as a popular blockchain-based virtual reality platform that enables users to monetize their content creation. However, a major criticism of these platforms is the low number of active users. Existing methodologies for measuring user traffic and engagement in these metaverse platforms are often unclear and inconsistent, and recent analyses do not provide a correct evaluation of the active users. In this paper, we propose a methodology for evaluating user traffic on decentralized metaverse platforms. Our approach employs a traffic monitor that links traffic with transactions to analyze user behavior. Decentraland has been used as a case study due to its decentralized nature and transparent provision of information about user traffic. The study includes an analysis of user behavior using graph analysis, as well as an examination of user traffic and transactions. We use user traffic to measure community engagement and economic activity, and we assess value exchange through parcel transaction prices. Our analysis indicates a lower average node degree in the interaction graph compared to traditional social media, no correlation between user traffic and parcel transaction prices, the exhibition of patterns of close proximity between the dates of traffic and transactions, and the presence of four distinct user clusters based on travel patterns, with the finding that a small proportion of highly engaged users contribute significantly to the total distance travelled. This study is the first to focus on user traffic and transaction activity within a metaverse platform, and the proposed methodology can be adapted for use on comparable metaverse platforms as well.