Who is leading China's family planning policy discourse in Weibo? A social media text mining analysis

Abstract

The advent of digital social media in China has altered our understanding of who sets the policy agenda and forms public opinion. Using text mining analysis of more than 74,000 Weibo user comments (over 4 million words) on 6 years' worth of The People's Daily media coverage, this study investigates social media interactions on family planning policy issues between the state-run news media and individual users in China. Our analysis demonstrates that Weibo postings about the topic by government-run news networks and comments by the general public are affecting each other, but also presenting partially reverse or bottom-up agenda-setting effects. Through latent dirichlet allocation (LDA) modeling, we identified major latent topic sets (women's right to work, family culture/tradition, law/regulation, and social welfare/wellbeing) and found that Weibo users' main concerns on China's family planning have changed over time. We also found that gender differences affect the topics of commenters.