Using merged IODA and KIO data across 155 countries (Jan 2018–Aug 2021), elections increase the daily probability of an Internet shutdown by a factor of 16, coups by a factor of roughly 300, and protests by a factor of 9. These political mobilization events do not increase the probability of spontaneous outages, providing a discriminating signal between intentional and unintentional disruptions.

Across all years of the KIO dataset (2016–2021), a large majority of events involved full-network shutdowns and their count grew significantly from 2016 to 2019 with no significant decline observed through 2021. Censors are also increasingly employing app-specific bans and throttling alongside full shutdowns, with all three restriction categories non-mutually exclusive and rising over the period.

§3.2, Figure 2 policy

The merged KIO-IODA dataset (Jan 2018–Aug 2021) documents 219 national-scale Internet shutdowns across 35 countries and 714 spontaneous outages across 150 countries; the 35 shutdown-affected countries collectively represent more than 1 billion estimated Internet users. Myanmar (53 IODA events), Syria (52), and Iraq (38) are the most frequently affected countries in the shutdown dataset.

§4, Table 2 evaluation

Countries where state-owned providers originate more than 50% of domestic address space show significantly higher shutdown prevalence; this state-ownership factor predicts shutdowns but shows no discernible difference for spontaneous outages. Countries with shutdowns have a median V-Dem liberal democracy score of 0.151 (maximum 0.481), compared to 0.279 for countries with spontaneous outages and 0.465 for countries with neither.

§5.1.1, Figures 8–9 policy

Over 55% of government-ordered shutdowns last a multiple of 30 minutes (vs. 15% of spontaneous outages), and 45% last precisely 4.5, 5.5, 8, or 10 hours (vs. <1% of spontaneous outages). The median recurrence interval between successive shutdown events within the same country is 1 day versus 39 days for spontaneous outages, with 67.7% of shutdowns falling exactly on 1-, 2-, 3-, or 4-day intervals versus 0.17% of outages.

§5.3, Figures 10–11 evaluation

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

Of 6,915,266 domains extracted from the 572 GiB Geedge Networks Leak (GNL), 298,955 censored domains (93.7% of all GNL-censored domains) appear in neither Tranco top-1M nor CitizenLab test lists. Measurements across China (Guangzhou/Nanjing), Myanmar, Pakistan, and Algeria confirmed censorship via DNS injection and SNI-based TLS connection termination. The GNL covers 25–62% of Tranco-censored domains across countries, showing substantial but incomplete overlap. This vendor-side ground truth reveals a censorship surface roughly two orders of magnitude larger than curated academic test lists.

2026-sheffey-geedge §4.1, Table 2 dpisni-blockingdns-poisoningmeasurement-platform

CensorAlert aggregates censorship signals from heterogeneous open sources — including OONI, Cloudflare Radar, NetBlocks, GitHub Issues of circumvention tools (Hysteria, Xray), Net4People BBS, NTC Party forum, Mastodon, X, Telegram channels, and arXiv — normalizing each item into a common schema preserving timestamp, source, raw data, and provenance with a link to the original content.

2026-zohaib-extended §2 (Data Sources) measurement-platform

Systematic measurement platforms (OONI, Censored Planet, Cloudflare Radar, NetBlocks) have inherent blind spots due to geographic coverage and protocol-specific test constraints; critical censorship discoveries — including GFW fully-encrypted protocol blocking and regional Chinese censorship — were first surfaced by user reports on forums and GitHub issue pages of circumvention tools, not by automated measurement infrastructure.

2026-zohaib-extended §1 measurement-platformfully-encrypted-detect

CensorAlert generates text embeddings (OpenAI text-embedding-3-small) from each item's summary, title, and tags to cluster semantically similar reports within configurable time windows; near-duplicates such as reposts, copied headlines, and translations are collapsed into a single canonical post that preserves all original source URLs and metadata.

2026-zohaib-extended §2 (AI-based Scoring) measurement-platform

CensorAlert's LLM agent scores each ingested item 0–5 on five independent dimensions — credibility, novelty, impact, timeliness, and verifiability — then computes a normalized significance score (0–10) from these components; items are processed every two hours using OpenAI GPT-5 Thinking (hosted on Azure) constrained to return structured JSON output.

2026-zohaib-extended §2 (AI-based Scoring) measurement-platform