Bluesky user attention mostly stays close in social network
Out-of-Network Attention Dynamics on Bluesky
Social and Information NetworksComputers and Society
Summary
Social media platforms often show you content based on who you follow, but sometimes you see posts from people you don't follow. The authors looked at a large set of interactions on Bluesky, a platform that shows posts mostly in reverse chronological order, and found that most interactions come from accounts very close to the users in the social network. While people sometimes explore content far beyond their immediate connections, this out-of-network attention rarely leads to new follower relationships. The study also shows that a small group of users is responsible for most of this exploration, and how exploration changes over time differs among individuals.
What this means in practice
- •For social media platform designers: Improve feed algorithms by accounting for how far attention travels in the follow graph to balance feed diversity and user engagement.
- •For digital marketing teams: Target campaigns by understanding that content rarely generates new followers beyond two network hops, refining outreach strategies.
Authors
Andrea Failla, Veronica Mesina, Giulio Rossetti
Abstract
Personalized social media commonly relies on explicit follow graphs to shape what content users encounter; yet how much attention crosses ties they have not formed remains largely undocumented at scale. We study this question on Bluesky, a large decentralized microblogging platform whose default feed relies on a simple, reverse-chronological content recommender. We analyze 173 million user-author interactions (likes, reposts, replies, and quotes) collected from a near-complete platform dump between February and September 2023. We decompose each interaction by attention-path length (already followed, relayed by a followed account, reachable within two follow-hops, or beyond) and find that 74.5% of interactions reach the user through an account they already follow. Measured by distance in the follow graph rather than by route, 80.6% of interaction lands within two follow hops, far beyond the 22.4% an expected-degree null predicts. We then characterize how exploration varies across users and over tenure. A broad-reaching minority generates three quarters of all exploratory activity, while aggregate declines in exploration with tenure mask three distinct individual trajectories. Finally, attention reaching beyond two hops converts into new follow ties at less than one third the rate of two-hop-local exploratory attention. Together, these results depict a platform where out-of-network exploration is substantial in volume but strongly constrained by network proximity and unlikely to translate into new social ties.