Datasets:

emperor-mew
/

global-censorship-index

license: cc-by-4.0
task_categories:
  - text-classification
  - question-answering
language:
  - en
tags:
  - internet-freedom
  - censorship
  - human-rights
  - network-measurements
  - ooni
pretty_name: Voidly Global Censorship Index
size_categories:
  - n<1K

Voidly Global Censorship Index

Real-time internet censorship measurements for 200 countries, based on 38,780,449+ OONI network probes.

Dataset Description

The Global Censorship Index provides country-level internet censorship scores derived from actual network measurements. Unlike annual expert assessments, this data updates daily.

Key Statistics

Countries covered: 200
Total measurements: 38,780,449
Severe censorship: 1 countries
High censorship: 6 countries
Update frequency: Daily

Most Censored Countries (Top 10)

Rank	Country	Score	Level
1	China	61%	severe
2	KG	48%	high
3	Iran	45%	high
4	Russia	37%	high
5	SS	37%	high
6	MU	33%	high
7	GA	31%	high
8	Venezuela	18%	medium
9	Myanmar	16%	medium
10	NP	16%	medium

Data Fields

country_code: ISO 3166-1 alpha-2 country code
country_name: Full country name
censorship_score: 0-100 score (100 = total censorship)
threat_level: Categorical level (free, low, medium, high, severe)
block_rate: Fraction of tested URLs blocked (0.0-1.0)
total_measurements: Number of OONI probe tests
blocked_measurements: Number of blocked test results
web_connectivity_tests: Website accessibility tests
telegram_tests: Telegram app connectivity tests
whatsapp_tests: WhatsApp connectivity tests
isp_count: Number of ISPs with data
top_blocking_isps: List of ISPs with highest block rates
rank: Global ranking by censorship severity

Scoring Methodology

Censorship scores are calculated from block rate percentages:

Score Range	Level	Description
0-4	Free	Minimal censorship
5-9	Low	Limited censorship
10-24	Medium	Moderate censorship
25-49	High	Significant censorship
50-100	Severe	Pervasive censorship

Data Sources

Primary: OONI (Open Observatory of Network Interference) - 38,780,449+ measurements
Supplementary: Distributed sensor network (16 nodes), anonymized VPN telemetry

Usage

from datasets import load_dataset

dataset = load_dataset("voidly/global-censorship-index")

# Get most censored countries
for entry in dataset['train']:
    if entry['threat_level'] == 'severe':
        print(f"{entry['country_name']}: {entry['censorship_score']}%")

Citation

@misc{voidly2025censorship,
  title={Global Censorship Index},
  author={Voidly Research},
  year={2025},
  url={https://voidly.ai/censorship-index},
  note={Data set. Updated daily.}
}

License

CC BY 4.0 - Free to use with attribution.