Abstract This article develops a comparative framework for measuring state influence as it appears within digital governance arrangements during pandemic communication. Rather than treating censorship, platform moderation, and narrative alignment as the same phenomenon, it separates them into two measures: the Information Control Index (ICI), which captures visible restriction, structured omission at monitored agenda nodes, and source concentration, and the Narrative Convergence Score (NCS), which captures alignment between official discourse and public discussion. The framework is applied to a China–US comparison during the COVID-19 pandemic (January 2020–December 2021) using retained corpora of approximately 86,000 Weibo posts, 93,000 tweets, 14,500 Chinese official texts, and 12,000 U.S. official texts. The article makes the analytical pipeline explicit by specifying source selection, keyword retrieval, retention criteria, language preprocessing, monthly aggregation, and index construction. The comparison confirms a familiar cross-national difference, but its main contribution is analytic and decompositional rather than merely descriptive: information control and narrative convergence do not move in lockstep and should therefore be measured separately. Across the monthly series, China records higher source concentration, stronger topical omission, and more stable official–public alignment, whereas the U.S. pattern is lower on both indices and more episodic, especially around acute health guidance and vaccine rollout. The article contributes a replicable strategy for comparative research on digital governance while clarifying what can and cannot be inferred from observable restriction, moderation, structured omission, and public narrative alignment.
Linsen Yang (Thu,) studied this question.