User Migration Across Web3 Online Social Networks: Behaviors and Influence of Hubs

• Main Authors: Galdeman, Alessia, Zignani, Matteo, Gaito, Sabrina
• Format: Conference Proceeding
• Language: English
• Subjects: Behavioral sciences; Blockchains; Buildings; financial networks; hubs; influence; Process control; Shape; Social networking (online); social networks; Soft sensors; user migration; Web3 online social networks
• ISSN: 1938-1883
• DOI: 10.1109/ICC45041.2023.10278763

The current online social network landscape is characterized by competition to get larger audiences leading to massive user migrations which will determine the shape of the future Web. However, user migration phenomena have not been fully understood and their driving mechanisms are still not well identified; in particular, the behaviors of hubs and the influence they exert on their followers are unclear. In this work, we focus on these aspects by analyzing the propensity of hubs to migrate towards a new social platform as a consequence of a shocking event; and the influence they exert on the decision of their neighbors of migrating to a new platform or staying on the native one. We conducted analysis on data made available after a user migration consequence of a hard fork involving two Web3 online social networks based on the blockchains Steem and Hive. Due to the blockchain nature of these Web3 platforms, we got detailed data about social and financial interactions among the users, along with information that allowed a precise reconstruction of the context surrounding the migration. The main findings suggest that different types of hubs apply different strategies when choosing to migrate, e.g. financial hubs diversify their strategy by staying and migrating at the same time. As for hub influence, results suggest that users directly interacting with hubs tend to migrate. In general, findings on influence indicate that understanding the activity and the influence of hubs is crucial in monitoring and controlling the user migration process.