Weibo employs keyword-based censorship with highly uneven application across topics: 82% of tweets in the Lushan topic (criticism of a local official) were censored, while 27 of 37 trending topics exhibited <2% censorship; overall ~1% of the 36.5M crawled tweets were censored. The Chinese government prioritizes censoring content that could incite public protest over content that is merely critical.

Censorship on Weibo does not produce a measurable chilling effect on discussion: Spearman's ρ = 0.198 (p = 0.011) between the percentage of censored tweets and unique tweeters per topic, indicating that censored topics attract more unique participants. No significant negative correlation was found for any of five engagement variables (comments per tweet, comments per user, total comments, unique commentors, unique tweeters).

§5.2, Table 3 evaluation

Comments on Weibo (~18M per day) are not independently censored: when a tweet is deleted, its comments are deleted as a cascade, but no instances of standalone comment censorship were observed in 36.5M tweets and associated comments. This creates a structural asymmetry — there are an order of magnitude more comments than tweets, yet comments persist unless their parent tweet is removed.

§2.3, §4.2 detection

Weibo users circumvent keyword-based censorship by substituting censored terms with morphs — abbreviations, anglicizations, homophones, homographs, and neologisms. 11 of 37 trending topics in a 44-day crawl of 280K users contained morphs, and morph usage was concentrated in heavily censored topics, with up to 5 morphs per topic observed.

§2.3, §6.1 defense

Morph adoption in censored topics begins within hours of censorship being imposed, and in some topics users adopt morphs preemptively before censorship is applied, demonstrating rapid community-level awareness of keyword filtering. Temporal analysis of the Lushan and Taxi topics (Figures 19–20) shows morph usage rising sharply in parallel with or ahead of censor action.

§6, Figures 19–20 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