BlueTempNet: A Temporal Multi-network Dataset of Social Interactions in Bluesky Social

Citation Author(s):
Ujun
Jeong
Arizona State University
Bohan
Jiang
Arizona State University
Zhen
Tan
Arizona State University
H. Russell
Bernard
Arizona State University
Huan
Liu
Arizona State University
Submitted by:
Ujun Jeong
Last updated:
Tue, 07/30/2024 - 17:43
DOI:
10.21227/yrsy-ee91
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Abstract 

Decentralized social media platforms like Bluesky Social (Bluesky) have made it possible to publicly disclose some user behaviors with millisecond-level precision. Embracing Bluesky's principles of open-source and open-data, we present the first collection of the temporal dynamics of user-driven social interactions. BlueTempNet integrates multiple types of networks into a single multi-network, including user-to-user interactions (following and blocking users) and user-to-community interactions (creating and joining communities). Communities are user-formed groups in custom Feeds, where users subscribe to posts aligned with their interests. Following Bluesky's public data policy, we collect existing Bluesky Feeds, including the users who liked and generated these Feeds, and provide tools to gather users' social interactions within a date range. This data-collection strategy captures past user behaviors and supports the future data collection of user behavior.

Funding Agency: 
ONR
Grant Number: 
N00014-21-1-4002