Where Have All the Paragraphs Gone? Detecting and Exposing Censorship in Chinese Translation
Authors: Mizhang Streisand (GFW Report), Eric Wustrow (University of Colorado Boulder), Amir Houmansadr (University of Massachusetts, Amherst)
Year: 2023
Issue: 1
Pages: 1–7
Abstract: Translated literature often gets cut or altered before being published in China. Worse yet, both readers and the original literature authors are not informed of such removal or changes most of the time. Such erasures can change the fundamental meaning of texts, and readers are left unaware of vital context. In this work, we propose an NLP-based approach to detecting translation censorship automatically and effectively. We further conduct a case study to analyze censorship in translated literature. We build a demonstration website and argue that an effective way to combat this form of censorship is to actively trigger the Streisand effect: by highlighting what text has been censored and making it easy to access, we hope the censored text reaches a broader audience, including those who would not have read the censored version in the first place.
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