Hashtag Re-Appropriation for Audience Control on Recommendation-Driven Social Media Xiaohongshu (rednote)

要旨

Algorithms have played a central role in personalized recommendations on social media. However, they also present significant obstacles for content creators trying to predict and manage their audience reach. This issue is particularly challenging for marginalized groups seeking to maintain safe spaces. Our study explores how women on Xiaohongshu (rednote), a recommendation-driven social platform, proactively re-appropriate hashtags (e.g., #宝宝辅食, Baby Supplemental Food) by using them in posts unrelated to their literal meaning. The hashtags were strategically chosen from topics that would be uninteresting to the male audience they wanted to block. Through a mixed-methods approach, we analyzed the practice of hashtag re-appropriation based on 5,800 collected posts and interviewed 24 active users from diverse backgrounds to uncover users' motivations and reactions towards the re-appropriation. This practice highlights how users can reclaim agency over content distribution on recommendation-driven platforms, offering insights into self-governance within algorithmic-centered power structures.

受賞
Honorable Mention
著者
Ruyuan Wan
Pennsylvania State University, State College, Pennsylvania, United States
Lingbo Tong
University of Notre Dame, South Bend, Indiana, United States
Tiffany Knearem
Google, San Francisco, California, United States
Toby Jia-Jun. Li
University of Notre Dame, Notre Dame, Indiana, United States
Ting-Hao Kenneth. Huang
Pennsylvania State University, University Park , Pennsylvania, United States
Qunfang Wu
Harvard University, Cambridge, Massachusetts, United States
DOI

10.1145/3706598.3713379

論文URL

https://dl.acm.org/doi/10.1145/3706598.3713379

動画

会議: CHI 2025

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2025.acm.org/)

セッション: Recommendation and Personalization

G401
7 件の発表
2025-04-29 20:10:00
2025-04-29 21:40:00
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