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下来的疑问。本研究详细阐述了如何通过收集埃隆·马斯克收购Twitter后前十周内从Twitter迁移至Mastodon的超过10,000名用户数据来探究这些问题。研究分为三个主要步骤：首先，我们开发算法以提取并分析迁移模式；其次，借助行为分析，考察Twitter与Mastodon的不同架构，以了解不同平台如何塑造各自平台上的用户行为；最后，我们确定哪些特定行为因素影响用户留在Mastodon。我们分享了用户迁移的发现、洞见，以及从用户行为研究中获得的经验教训。