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，引发了关于迁移模式特征、不同平台对用户行为的影响以及迁移用户如何在迁移过程中安顿等问题。本研究通过收集Twitter所有权变更后前十周内从Twitter迁移至Mastodon的超过10,000名用户数据，详细阐述了如何探究这些问题。我们的研究分为三个主要步骤：首先，开发算法以提取和分析迁移模式；其次，利用行为分析方法，考察Twitter与Mastodon的不同架构，学习用户行为如何与各平台特性相对应；最后，确定特定行为因素如何影响用户留在Mastodon。我们分享了用户迁移的发现、见解以及从用户行为研究中获得的经验教训。