Temporal Multi-network of Social Interactions in Bluesky Social (BlueTempNet) Dataset

With the advent of decentralized social media platforms such as Bluesky Social (hereafter referred to as Bluesky), there is official support for the public disclosure of user activities with millisecond-level timestamps. Based on the principles of open-source and open-data conditions of Bluesky, our study presents the first integration of the temporal dynamics of users' social interactions, such as blocking, following, and grouping (community formation), into a multi-network. Here, a community is defined as custom Feeds that users bookmark to receive posts of interest. Our methodology involves collecting all existing Bluesky Feeds, including users who liked and generated these Feeds, and providing tools to gather users' interactions within specified date ranges. This approach captures past user activities and supports the ongoing collection of user behavior for the future.