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 on how we investigate these questions by collecting data over 10,000 users who migrated from Twitter to Mastodon within the first ten weeks following the ownership change of Twitter. Our research is structured in three primary steps. First, we develop algorithms to extract and analyze migration patterns. Second, by leveraging behavioral analysis, we examine the distinct architectures of Twitter and Mastodon to learn how user behaviors correspond with the characteristics of 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等替代平台的现象，引发了关于迁移模式特征、不同平台如何影响用户行为、以及迁移用户如何在迁移过程中实现稳定的研究问题。本研究通过收集Twitter所有权变更后前十周内从Twitter迁移至Mastodon的逾万名用户数据，详细阐述了针对上述问题的探究方法。研究分为三个核心步骤：首先，我们开发算法以提取并分析迁移模式；其次，通过行为分析手段，对比Twitter与Mastodon的差异化架构，揭示用户行为与各平台特性之间的对应关系；最后，我们确定影响用户长期留存于Mastodon的关键行为因素。本文分享了用户迁移行为研究的发现、洞见及经验总结。