Abstract
Abstract: This study investigates the phenomenon of information homogenization on Chinese social media platforms, specifically focusing on Weibo and Zhihu. As two of Chinas largest and most influential platforms, they provide contrasting environmentsWeibo for mass, entertainment-driven content, and Zhihu for in-depth knowledge discussing and sharing. By analyzing data from both platforms between July 2022 and April 2024 using natural language processing and Latent Dirichlet Allocation (LDA) models, this research reveals that information homogenization has increased on Zhihu, driven by concentrated discussions around a few trending topics, and the corresponding push strategies of online platforms. In contrast, Weibo has maintained a relatively stable, high degree of homogenization throughout the period. These trends highlight the growing challenge of content diversity on Chinese social networks, posing implications for both users and platforms. The findings underscore the need for strategies that balance user engagement with the promotion of diverse content, contributing to a healthier online ecosystem and better information consumption.
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