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Xiaohongshu users attribute audience changes to algorithms and social actors

By PulseAugur Editorial · [1 sources] ·

A new arXiv paper explores how users on the social platform Xiaohongshu perceive and react to changes in their audience composition. Researchers analyzed comments to understand how users attributed these changes, distinguishing between algorithmic factors and social actors. The study found a strong correlation between how users explained audience shifts and the boundary-management strategies they employed, such as technical adjustments or social enforcement. AI

IMPACT Provides insights into user behavior and community governance on AI-driven recommendation platforms.

RANK_REASON Academic paper on social platform dynamics and user attribution. [lever_c_demoted from research: ic=1 ai=0.4]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Xiaohongshu users attribute audience changes to algorithms and social actors

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Academic paper on social platform dynamics and user attribution. [lever_c_demoted from research: ic=1 ai=0.4]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Zhiyi Zhou, Kyrie Zhou ·

    Making Sense of Audience Change: Causal Attribution and Boundary Management on Xiaohongshu

    arXiv:2610.38026v1 Announce Type: cross Abstract: Recommendation-driven platforms can reshape not only what users see, but also who becomes visible and how community boundaries are negotiated. We examine Xiaohongshu discussions surrounding a perceived World Cup-related audience i…

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