Censors on Sina Weibo were documented retroactively removing entire repost cascades started from a single sensitive post. Extrapolating from sampled data, prior work estimated that up to 4,200 workers working eight-hour shifts would be required to match the censorship demand on Sina Weibo alone, with documented peak hours for deletion activity.

Cascade-based censorship (ICM model) and uniform random deletion produce measurably different topological signatures: cascade removal causes greater increases in network diameter and radius as the censorship fraction γ increases and a substantial increase in assortativity at mid-removal levels (γ=0.2–0.5), whereas uniform deletion shows slower, more gradual changes across these same metrics.

§4.1 evaluation

An SVM classifier using a 60-dimensional feature vector — 10 topological network metrics (assortativity, clustering coefficient, diameter, radius, betweenness centrality, degree distribution exponents) plus 50 Laplacian eigenvalues — can detect network-level censorship without any content analysis. The classifier successfully distinguishes censored from uncensored reply-graphs even at the lowest tested censorship level of γ=0.1 (10% edge removal), using 10-fold cross-validation repeated 10 times.

§3–4 detection

A random sample of Sina Weibo messages found that 16.25% were deleted overall, with geographic distribution having a strong impact: up to 53% of messages from some Chinese provinces were deleted. Nearly 30% of all deletions occurred within the first 5–30 minutes of posting, and up to 90% within 24 hours of the posting.

§2 Related work evaluation

During the June 2025 shutdown, Iranian authorities blocked international One-Time Password (OTP) SMS delivery, preventing new sign-ins to foreign secure-messaging platforms and VPN services. This forced users toward government-approved domestic platforms that lack security and privacy protections. The blockade of OTPs effectively weaponized account-recovery flows as a secondary shutdown layer, disproportionately affecting users who needed to activate new circumvention tools during the crisis.

2025-iran-shutdown-measurement §Human Rights Implications port-blockingdpikeyword-filtering

Simple character-level perturbations (English) and homophone substitutions (Chinese), combined with LLM instruction-following prompts directing the model to use word substitutions in its output, successfully bypassed all input and output filters for all 41 input-blocked and 197 output-blocked queries across five major Chinese LLM services (Baidu-Chat, DeepSeek, Doubao, Kimi, Qwen). Every input-blocked query contained at least one keyword combination that alone triggered the filter, confirming keyword-matching rather than semantic classification.

2026-ablove-characterizing §VII-D keyword-filtering

Cross-national experiments conducted from Singapore, South Korea, and Taiwan during February 19–24, 2025 found no variance in blocking implementations, event syntax, or server infrastructure across all five Chinese LLM services. Input blocking was enacted identically in all three international locations, and services connected to the exact same server IP addresses globally — Kimi and Baidu-Chat connected to identical IPs and DeepSeek to the same two addresses across all tested locations.

2026-ablove-characterizing §VIII-A keyword-filtering

Input blocking in Chinese LLM services (DeepSeek, Qwen, Kimi, Doubao) is overwhelmingly consistent: all four services persistently block the exact same queries across all 5 measurement samples in both Simplified and Traditional Chinese. Output blocking is far less consistent, with only 29 out of 349 output-blocked queries blocked across all 5 samples. Baidu-Chat is exceptional: it performs almost no input blocking but instead relies heavily on post-search and output blocking (78.6% of blocks are output-phase).

2026-ablove-characterizing §VI-B keyword-filteringdpi

DeepSeek, Kimi, and Doubao all transmit analytics logs to the same Autonomous System (AS24429, Zhejiang Taobao Network Co., Ltd., a ByteDance/Volcengine subsidiary), with one monitoring endpoint IP directly overlapping between DeepSeek and Doubao. Additionally, all four non-Qwen services maintain connections with servers physically located in China throughout the chat session, transmitting user IDs, session IDs, viewport data, language preferences, and in Baidu-Chat's case, the full query text via URL-encoded CAPTCHA requests.

2026-ablove-characterizing §VI-D keyword-filtering

All five Chinese LLM services transmit partial or complete responses to the client machine even when output blocking is triggered, representing a major information leak. For DeepSeek and Qwen, truncated blocked responses are on average close in token length to full successful responses. For Baidu-Chat, the complete response is transmitted to the client but only partially rendered in the browser UI, with only a word or two visible on screen.

2026-ablove-characterizing §VI-C keyword-filtering