The Diffusion of Expert Opinion and the Risk of Echo Chambers

This paper investigates the role country experts, and their social networks, play in the research of authoritarian regimes. With many such regimes becoming harder to access, experts have become an ever more important source of information and analysis to understand and predict regime behavior. These experts will have a strong potential influence on the policies of foreign actors towards the autocratic regime. Our data focuses on China. Understanding Chinese politics has become increasingly important for policymakers as China has become a leading cultural, economic, and political global power. Experts in Chinese politics therefore play an important role as a source of information, analysis, and guidance. While experts may directly observe politics in China, they also inform and are informed by each other. This creates an opportunity for the diffusion of knowledge and information within a network, such as through publications, conferences, social media and other opportunities for observation and dialogue. However, it also creates a risk that sharing and amplifying inaccurate information or biased assessments within the network results in sub-optimal policy outcomes. Furthermore, the experts’ specific educational, geographic and socio-economic background may influence their view, as might their connections to government and opposition sources. We use a snowball sampling process using recommendations to accumulate information on over 2,000 individual China experts globally. The data contains self-reported assessments of their own expertise on Chinese politics from almost 500 respondents, and occupational background information from public sources on most of the nominated individuals. We also use the nominations to construct a network through which information and influence could potentially flow within this community. We scrape blog-style publications of experts on salient issues in Chinese politics from online publications and blogs, as well as Twitter feeds, and apply topic modelling to investigate the nature of the information flow through the network. A Stochastic Actor-Oriented Model (SAOM) is used to estimate the level and shape of information diffusion across the network of experts. The findings indicate the presence of the diffusion of writings among networks of experts on Chinese politics, signifying a considerable potential for the existence of echo chambers among these experts. As a robustness check, we replicate the analysis with a network that changes over time, using the China experts’ posts and follower/following networks from Twitter/X, collected live until June 2023.