Research on User Behavior Analysis and Operational Optimization of University Metaverse Platforms—An Empirical Analysis Based on SUESMC Server

Abstract

With the proposal of the concept of "university metaverse" in recent years, Minecraft, as a youthful metaverse creation platform, has gradually attracted the attention of major universities. Taking the SUESMC server as an example, this paper analyzes player behavior using MDA theory and the difference-in-differences method based on Plan plugin data and questionnaire results. The study finds that although offline activities can promote user growth, the retention rate significantly declines after the activities; in addition, user needs are obviously differentiated. Social players are the core of community stickiness, while achievement-oriented and exploration-oriented players are lost due to resource monopoly, homogeneous gameplay, and lagging map updates. Based on this, the study proposes optimization strategies in three aspects: mechanism, operation, and technology, including feasible strategies such as phased guidance, dynamic resource refresh, high-frequency activity iteration, and AI application, providing some practical references for the construction and operation of university metaverse communities.