Survival analysis of 423,265 pages with Wayback Machine histories shows pages on politically controversial topics have substantially shorter lifetimes than those on uncontroversial topics; topic change — not just page deletion — must be treated as 'death' for probe-list purposes, since a page that switches topic no longer contains the sensitive material that made it censorship-relevant.

China's Great Firewall adds sites to its blacklist within hours of their becoming newsworthy and drops them again just as quickly; conversely, Pakistan's pornography crackdown used a rarely-updated blocklist, causing 50% of consumption to shift to unlisted sites. An outdated probe list will therefore underestimate GFW effectiveness and overestimate effectiveness in countries with static lists.

§1 detection

Analysis of 758,191 URLs across 22 probe lists found near-zero URL-level Jaccard similarity between nearly all list pairs (most < 0.01), including between country blacklists; even at hostname level, blacklists share little with each other or with researcher-curated lists like ONI's 12,107-URL list, indicating that any single probe list systematically misses large portions of what is actually censored.

§3.3, Tables 1–2 evaluation

Topic correlation analysis across 2,904 list-topic pairs (585 significant after Bonferroni correction at α = 0.05) shows social media is disproportionately represented in country blacklists relative to the broader web; video-sharing sites are also frequently blocked, likely to suppress political organization, copyright infringement, or competition with local businesses.

§7.1, Table 3 detection

Syria's 2015 blocklist contained a disproportionately large share of software-related sites because censors applied indiscriminate TLD-based blocking of all .il (Israeli) domain names regardless of content, demonstrating that non-topic-based criteria (country-code TLD, ASN) can sweep in entirely unrelated infrastructure and are detectable only through anomaly spot-checks rather than content analysis.

§7.1 detection

'Resource Inaccessible' was the most frequently reported issue (61% of 119 submitted reports) during a month of naturalistic Tor Browser browsing, followed by CAPTCHAs (18%), Broken Content (17%), Other Issues (13%), and Timeouts (5%). These categories document the operational failure modes that degrade everyday Tor Browser usability beyond protocol-level censorship.

2026-micallef-reportor-facilitating-user §6.1, Figure 3 ip-blockingmeasurement-platform

The privacy properties of Tor Browser structurally preclude automated telemetry collection, creating a persistent blind spot for diagnosing user experience failures at scale. ReporTor demonstrates that anonymous voluntary in-situ reporting — transmitted over the Tor network and stored in a password-protected onion-service database — can substitute for telemetry: 119 reports over one month from five expert users sufficed to reproduce approximately half of reported issues exactly and identify root causes for most of the remainder.

2026-micallef-reportor-facilitating-user §1, §7.1 measurement-platform

A compiled blocklist dataset documents 43,083 apex domains blocked via DNS filtering across 6 Indian ISPs, representing one of the largest systematic inventories of Indian DNS censorship scope published to date.

2026-qurbat-list-domains-blocked compiled_blocklist.csv (main dataset) dns-poisoningmeasurement-platform

The dataset incorporates Tranco popularity rankings for blocked domains (derived from the 'Poisoned Wells' research), enabling measurement of how DNS blocking in India intersects with high-traffic websites rather than being confined to obscure domains.

2026-qurbat-list-domains-blocked Abstract (Tranco ranking annotation) dns-poisoningmeasurement-platform

The blocklist spans 6 distinct Indian ISPs, enabling cross-ISP consistency analysis; the multi-ISP scope reflects that DNS-based blocking in India is implemented heterogeneously at the ISP level rather than via a single national chokepoint.

2026-qurbat-list-domains-blocked Abstract / dataset metadata dns-poisoningmeasurement-platform

The largest single source of censored domains in the GNL is MESA lab's SNI monitoring dataset (E21-SNI-Top200w.txt) containing 57,362 censored domains, and E21-SNI-Top120W-20221020.txt with 36,467 domains—totaling over 93K domains from network tap data alone for a single country (E21 = Ethiopia per InterSecLab attribution). A separate Xinjiang dataset (XJ-CUCC-SNI-Top200w.txt) contains 13,604 domains. These datasets "do not seem to come from popular domain lists, and instead appear to be gathered from network taps," confirming that Geedge builds censorship target lists directly from passive traffic observation.

2026-sheffey-geedge §4.2, Table 3 dpisni-blockingmeasurement-platform