Research Article

Research on the Homogenization of Network Information Based on Chinese Social Media Weibo and Zhihu

Minxing GuWuhan University*

* Corresponding author: [email protected]

Abstract

This study investigates the phenomenon of information homogenization on Chinese social media platforms, specifically focusing on Weibo and Zhihu. As two of China’s largest and most influential platforms, they provide contrasting environments—Weibo 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.

Keywords: Homogenization; Social Media; Network Information.
Published: November 15, 2024
DOI: 10.54254/2753-7064/42/20242501
Volume: CHR Vol.42
pp. 102-108
Download PDF

References

  1. Kossinets, G & Watts, D. Origins of homophily in an evolving social network. Journal of Sociology, 2009,115(2), 405–450.
  2. McEwan, B. Carpentier, J & Hopke, E. Mediated skewed diffusion of issues information: A theory. Social Media + Society,2018,4(3), 1–4.
  3. Mikal, P. Rice, E & Kent, G. Common voice: Analysis of behavior modification and content convergence in a popular online community. Computers in Human Behavior, 2014(35), 506–515.
  4. Hosanagar, K. Fleder & D. Lee, D. Will the global village fracture into tribes? Recommender systems and their effects on consumer fragmentation. Management Science, 2014,60(4), 805–823.
  5. Airoldi, M., Beraldo, D & Gandini, A. Follow the algorithm: An exploratory investigation of music on YouTube. Poetics, 2016,57, 1–13.
  6. Scheufele, A & Nisbet, C. Commentary: Online news and the demise of political disagreement. Annals of the International Communication Association, 2013,36(1), 45–53.
  7. Cheng Shian, Shen Enshao. Explanation and Reconstruction of Organizational Communication Theory in the Digital Era: From the Perspective of Technological Progress and the Evolution of Communication Laws. Journalism University, 2009(2):119-124.
  8. Yao Wenkang. The "Information Cocoon" Effect and Reflections on Aggregated News Apps: A Case Study of "Today’s Headlines". Media Forum, 2020(3):151-153.
  9. Xu Xiang, Ao Ziqi, Shi Jingyuan, et al. Convergence Through Different Paths: Homogenization of Information Coccoons in User-Generated Content on Social Media—An Empirical Analysis Based on Sina Weibo. Journal of Xi'an Jiaotong University (Social Science Edition), 2022, 42(03):133-140.
  10. Jiang Zhongbo, Xue Danyang. Analysis of the "Echo Chamber" and "Filter Bubble" in the Era of Social Media. Journalism and Communication Review, 2024, 77(03):101-114.