In the online age, autocracies' censors must manage abundant information. At the same time, they face consumers with varying valuations for investigative content. This paper reveals a strategic pattern in the placement of news within Chinese online newspapers (2020-22). Studying over a million articles from 53 news outlets, I show that front-page articles are more likely to feature content favoured by the government relative to articles published in other locations of news websites. Different text-based measures are employed to determine each article's alignment with the government's preferred content: Citing the government's press agency, Xinhua, makes an article approximately eight percentage points more likely to feature on the front-page. Similarly, a one-standard-deviation decrease in the resemblance with foreign content on China increases the front-page placement probability by 1.1 percentage points. Both theoretical and empirical evidence suggest that foreign information sources -- costly but not impossible to access for an investigative minority of readers -- influence domestic censorship strategies.
About the series
The CIVICA Data Science seminar series is an interdisciplinary forum of the CIVICA European University of Social Sciences, an alliance of eight leading higher education and research institutions. The series fosters a community of researchers, practitioners, and policymakers working to address complex societal challenges through the use of novel methodological and data-driven approaches, drawing from machine learning and quantitative methods from biology, sociology, political sciences, economics, and physics, among other disciplines. Shared among the partner institutions of the CIVICA network, this series directly addresses the data science research stream of the CIVICA initiative.
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