Bluesky: Network topology, polarization, and algorithmic curation.

2024-05-27

PLoS ONE

AI Summary

This study addresses the lack of empirical analysis on political communication dynamics in decentralized social platforms. We conduct the first systematic, multi-layer network analysis—encompassing replies, likes, reposts, and follows—of 5 million Bluesky users (February 2023–May 2024), integrating custom algorithmic feeds, ideological embeddings, hyperlink provenance tracing, and small-world modeling. Methodologically, we apply social network analysis to characterize topology (high clustering, short average path length, heavy-tailed degree distribution), quantify feed adoption rates, map source ideology via domain-level political alignment, and model temporal polarization using co-engagement networks. Results reveal: (1) minimal usage of user-curated feeds; (2) shared links predominantly originate from center-left sources with no evidence of amplified disinformation; and (3) pronounced issue-based homophily and dynamic bipartite polarization on Israel–Palestine content—yielding a paradoxical “strong issue polarization, weak source polarization” pattern. These findings provide novel empirical evidence and an analytical framework for understanding algorithmic governance and political discourse in decentralized platforms.

Technology Category

• Data Mining & Knowledge Management: Graph Mining, Social Network Analysis & Community
• Application Domains: Humanities & Computational Social Science
• Natural Language Processing: Discourse, Pragmatics & Argument Mining

Application Category

• Social Networks and Social Media: Media and governance, opinion dynamics, filter bubbles, polarization
• Web Mining and Content Analysis: Content-based information diffusion
• Systems and Infrastructure for Web, Mobile and WoT: Decentralized Web and Fediverse systems

Abstract

Bluesky is a nascent "Twitter-like" and decentralized social media network with novel features and unprecedented data access. This paper provides a characterization of its interaction network, studying the political leaning, polarization, network structure, and algorithmic curation mechanisms of five million users. The dataset spans from the website's first release in February of 2023 to May of 2024. We investigate the replies, likes, reposts, and follows layers of the Bluesky network. We find that all networks are characterized by heavy-tailed distributions, high clustering, and short connection paths, similar to other larger social networks. BlueSky introduced feeds-algorithmic content recommenders created for and by users. We analyze all feeds and find that while a large number of custom feeds have been created, users' uptake of them appears to be limited. We analyze the hyperlinks shared by BlueSky's users and find no evidence of polarization in terms of the political leaning of the news sources they share. They share predominantly left-center news sources and little to no links associated with questionable news sources. In contrast to the homogeneous political ideology, we find significant issues-based divergence by studying opinions related to the Israel-Palestine conflict. Two clear homophilic clusters emerge: Pro-Palestinian voices outnumber pro-Israeli users, and the proportion has increased. We conclude by claiming that Bluesky-for all its novel features-is very similar in its network structure to existing and larger social media sites and provides unprecedented research opportunities for social scientists, network scientists, and political scientists alike.

Problem

• Characterizes Bluesky's interaction network and political polarization.
• Analyzes algorithmic curation and user engagement with custom feeds.
• Investigates network structure and ideological divergence in user opinions.

Innovation

• Decentralized social media network analysis
• Algorithmic content recommendation feeds
• Political and issue-based network polarization study