During the Sri Lanka social-media block following the April 21, 2019 bombings, Censored Planet measured HTTP(S) censorship jumping from 0.1% to 2% in one week and discovered 22 blocked domains versus the 7 reported by NetBlocks and AccessNow; 5 of those extra domains were only present in the Alexa top-sites list, not the Citizen Lab Global Test List. Blocking remained elevated through May 12, 2019, contradicting public reports that the ban was lifted by May 1st.

Censored Planet collected 21.8 billion measurements over 20 months from more than 95,000 vantage points in 221 countries, covering 66–173 more countries than OONI and ICLab, with a median of 8 ASes per country versus OONI's 4 and ICLab's 1. In March 2020, it achieved coverage of 9,014 ASes compared to OONI's 1,915. Censored Planet and OONI together covered all 21 countries rated 'Not Free' by Freedom House, while ICLab reached only 4.

§6.1, §6.2 evaluation

Of 21.8 billion raw measurements, approximately 7% (1.5 billion) were initially flagged as blocked; iterative HTML clustering and DBSCAN image clustering then removed ~500 million false positives, leaving ~1 billion confirmed blocked measurements. The clustering process formed 457 new response clusters, of which 308 were confirmed blockpages and 149 were false positives, with Cloudflare bot-checks being a notable source of false positives in HTTPS measurements.

§5.1.3, §5.1.4 evaluation

Mann-Kendall trend analysis at 99% significance on 20 months of data found increasing censorship activity in more than 100 countries, driven primarily by DNS and HTTPS blocking methods, and identified 11 website categories facing rising censorship including human rights content, news media, and provocative attire. Countries such as Norway (ranked #1 in press freedom) showed aggressive DNS blocking across 25 ASes targeting more than 50 domains in at least 6 categories including hrw.org.

§7.2, §7.1.2 evaluation

Censored Planet achieves 93% /24 vantage-point continuity and 99.01% AS continuity between weekly scans, versus ICLab's 64% and OONI's 36% AS continuity. Applying bitmap-based anomaly detection on the resulting longitudinal time series detected 15 prominent censorship events over 20 months, two-thirds of which had not been previously reported, while OONI data showed no corresponding increase for most newly discovered events due to sparse volunteer measurements.

§5.3, §6.1, §7.1 evaluation

The paper proposes a black-box methodology for detecting censorship bias in LLMs by comparing responses to identical prompts in Simplified vs. Traditional Chinese — scripts for the same spoken language — controlling for translation quality while exploiting that Simplified Chinese training data is disproportionately sourced from mainland China's censored internet. Each prompt is repeated ten times and scored for similarity to censored text using an XLM-RoBERTa classifier fine-tuned on Baidu Baike (censored) vs. Chinese Wikipedia (uncensored) with scores from 0 to 1.

2024-ahmed-extended §2 / §2.4 keyword-filteringml-classifiermeasurement-platform

The paper proposes detecting translation censorship by back-translating the Chinese text to English via Google Translate, embedding each paragraph with distiluse-base-multilingual-cased-v1, and solving a linear-sum-assignment bipartite matching weighted by negated cosine similarity. Paragraphs below a similarity threshold are flagged as cut; matched paragraphs are recursively compared at sentence level to detect alterations.

2023-streisand-where §2 Methodology keyword-filteringmeasurement-platform

Hong Kong Twitter users are 33% more likely than a random control sample to have protected their accounts, and over 247% more likely to have deleted past Tweets, after enactment of the June 2020 national security law (NSL). These differences are statistically significant at p ≤ 1.74e-48 for all account-protection and Tweet-deletion metrics.

2023-wang-self-censorship §4.1 / Table 2 keyword-filteringmeasurement-platform

Hong Kong Twitter discussion of COVID-19 continued declining after mid-2020 and did not resurge during Hong Kong's large March 2022 COVID wave, unlike the control group whose COVID discussion tracked local transmission rates. The authors interpret this anomalous pattern as a generalized chilling effect: NSL legal risk suppressed even politically ambiguous health discussion that mainland China had censored but that may not clearly fall under the NSL.

2023-wang-self-censorship §4.2 / Figure 2c keyword-filteringmeasurement-platform

Of inaccessible Tweets from 2019, those containing NSL-sensitive political keywords are disproportionately deleted or protected by both Hong Kong users (36.38% inaccessibility) and Taipei users (34.89%), compared to New York City (29.45%) and Tokyo (30.80%). This suggests that NSL legal exposure — which extends extraterritorially under Article 38 — may be chilling speech even among users outside Hong Kong who transit or have ties to mainland China.

2023-wang-self-censorship §4.1 / Table 3 keyword-filteringmeasurement-platform

While Hong Kong users sharply reduced discussion of NSL-sensitive political topics after July 2020, their rate of Tweeting about non-sensitive topics (travel, food, art, media) remained stable and mirrored control-group trends. This targeted suppression — rather than a general withdrawal from Twitter — confirms the NSL produced specific self-censorship of covered speech rather than platform abandonment.

2023-wang-self-censorship §4.2 / Figure 2b keyword-filteringmeasurement-platform