When LLMs Enter Everyday Feminism on Chinese Social Media: Opportunities and Risks for Women's Empowerment

2026-02-24

AI Summary

This study investigates the dual role of large language models (LLMs) in everyday feminist practices on Chinese social media, where they may simultaneously empower women and reinforce gender biases. Drawing on a dataset of 430 posts from Xiaohongshu, 139 LLM-generated texts produced by DeepSeek, and 3,211 user comments, the research integrates feminist critical discourse analysis with user interaction analysis. It reveals, for the first time in a non-Western context, that while LLMs ostensibly support women’s empowerment, they often steer users toward internalizing dominant sociocultural norms rather than challenging structural inequalities. Findings indicate that users frequently adopt LLM suggestions, yet these recommendations predominantly emphasize individual self-optimization over collective social change. The study offers critical insights for designing AI systems that are more critically reflective and genuinely empowering in feminist contexts.

Technology Category

• Machine Learning: Large Multimodal Models (LMMs)
• Natural Language Processing: (Large) Language Models
• Cognitive Modeling & Cognitive Systems: Social Cognition And Interaction

Application Category

• User Modeling, Personalization and Recommendation: Large Language Models (LLM) for user modeling and recommendation
• Social Networks and Social Media: Generative AI / large language models and their impact on social systems
• Economics, Online Markets and Human Computation: Cost models of using LLMs in production systems

Abstract

Everyday digital feminism refers to the ordinary, often pragmatic ways women articulate lived experiences and cultivate solidarity in online spaces. In China, such practices flourish on RedNote through discussions under hashtags like''women's growth''. Recently, DeepSeek-generated content has been taken up as a new voice in these conversations. Given widely recognized gender biases in LLMs, this raises critical concerns about how LLMs interact with everyday feminist practices. Through an analysis of 430 RedNote posts, 139 shared DeepSeek responses, and 3211 comments, we found that users predominantly welcomed DeepSeek's advice. Yet feminist critical discourse analysis revealed that these responses primarily encouraged women to self-optimize and pursue achievements within prevailing norms rather than challenge them. By interpreting this case, we discuss the opportunities and risks that LLMs introduce for everyday feminism as a pathway toward women's empowerment, and offer design implications for leveraging LLMs to better support such practices.

Problem

• large language models
• everyday feminism
• women's empowerment
• gender bias
• social media

Innovation

• large language models
• everyday feminism
• women's empowerment
• gender bias
• social media discourse