AI & ML
Low-vocality Engagement and Participation Dynamics on Bluesky
arXiv cs.HC0 views
arXiv:2606.21665v2 Announce Type: replace-cross Abstract: Online participation is often measured through visible expression, especially posting, yet many consequential forms of engagement occur through less vocal actions such as liking and following. Here we study how users inhabit Bluesky by reconstructing participation profiles from more than three billion activity records produced by a near-complete sample accounting for more than 80\% of registered users. We aggregate behavior into monthly user-level observations and distinguish two dimensions that are often conflated in platform analytics: intensity, capturing how much users engage, and style, capturing how engagement is expressed across actions. We find that vocal production is highly concentrated, but low-posting behavior does not imply absence from platform participation. High-intensity engagement is most strongly associated with liking rather than posting, while posting-oriented participation is more common among low-intensity users, indicating that visibility and sustained engagement should not be conflated. Transition patterns suggest that high-intensity likers and posters could be described as attractors; network-building redirects users within the active space; whereas observed inactivity acts as a persistent boundary that selectively limits re-entry. Higher-order motifs further show that inactivity often interrupts rather than erases prior regimes, and that low-intensity liking can precede durable high-intensity engagement. These results show that online participation is structured by differentiated low-vocality practices, calling for a shift from post-centered measures of activity toward dynamic accounts of platform presence. We identify a broader challenge for computational social science: platform participation cannot be adequately understood through the behavior of vocal minorities alone.
Source:https://arxiv.org/abs/2606.21665PreviousA Cross-Country Evaluation of Sentiment Toward Digital Payment Systems in AfricaNextJYVA at BeTraC: Audio-Based Medical Note Generation with SOAP Section-Specific Queries
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