A recent surge of users migrating from Twitter to alternative platforms, such as Mastodon, raised questions regarding what migration patterns are, how different platforms impact user behaviors, and how migrated users settle in the migration process. In this study, we elaborate how we investigate these questions by collecting data over 10,000 users who migrated from Twitter to Mastodon within the first ten weeks following Elon Musk's acquisition of Twitter. Our research is structured in three primary steps. First, we develop algorithms to extract and analyze migration patters. Second, by leveraging behavioral analysis, we examine the distinct architectures of Twitter and Mastodon to learn how different platforms shape user behaviors on each platform. Last, we determine how particular behavioral factors influence users to stay on Mastodon. We share our findings of user migration, insights, and lessons learned from the user behavior study.

翻译：近期大量用户从Twitter迁移至Mastodon等替代平台，引发了对迁移模式特征、不同平台如何影响用户行为，以及迁移用户在迁移过程中的适应状况等问题的探讨。本研究通过收集埃隆·马斯克收购Twitter后前10周内从Twitter迁移至Mastodon的逾1万名用户数据，系统阐述了如何探究上述问题。我们的研究按三个主要步骤展开：首先，开发算法以提取并分析迁移模式；其次，通过行为分析，对比Twitter与Mastodon的差异化架构，揭示不同平台如何塑造用户行为特征；最后，确定哪些特定行为因素会促使用户持续使用Mastodon。本文分享了用户迁移的研究发现、相关洞见，以及从此次用户行为研究中汲取的经验教训。