GDELT daily event-roots mix by country
Daily per-country decomposition of GDELT world events by CAMEO root event category, from the GDELT Project's keyless 2.1 event update files: the trailing complete UTC day's root events (IsRootEvent=1, GLOBALEVENTID-deduped) resolved to ISO countries via the embedded FIPS 10-4 crosswalk, aggregated per (country, event root) into event counts, article volume, mean AvgTone (-100..100) and Goldstein scale (-10..10), negative-tone share, QuadClass 3/4 conflict and 1/2 cooperation shares, each cell's share of its country's daily coverage, a 0-100 Herfindahl mix-concentration score (100 = every event in one category), and a deterministic root_rank within each country (1 = most events). (Country, root) cells below 3 events and countries below 5 daily events are gated out; zero nulls. Coverage: ~150-220 countries/day depending on the news cycle; units are counts, shares in percent, scores 0-100. Caveats: GDELT coverage varies by language and over time, so volume is media attention as much as event count; AvgTone is a dictionary measure, not sentiment itself. Only event metadata and aggregates — no article bodies, no per-row URLs. GDELT terms require citation of the GDELT Project and a link to https://www.gdeltproject.org/. Sample use: filter event_root in ('14','18','19','20') for daily conflict-event intensity by country, or order by mix_concentration desc for the most one-story-dominated coverage.
- Rows
- 1,069
- Columns
- 19
- Source cadence
- Daily
- Last refreshed
- Sep 27, 2026
- Theme
- news
| Column | Type | Description |
|---|---|---|
| date | string | Window date (the single trailing complete UTC day), YYYY-MM-DD; primary key together with country_code and event_root. (unit: date) |
| as_of | string | Window-end date (the trailing complete UTC day), YYYY-MM-DD; identical to date for the daily grain. (unit: date) |
| fetched_at | string | Day-granular fetch stamp: window-end midnight UTC. Any run rebuilding the same window produces the identical stamp, so re-ingests are true no-ops. (unit: timestamp) |
| country_code | string | ISO 3166-1 alpha-3 country code; primary key together with date and event_root. Resolved from GDELT FIPS 10-4 codes with documented divergences (UK->GBR, GM->DEU) and Kosovo as XKS. (unit: iso-alpha-3) |
| country_name | string | Canonical English country name from the hub.normalize country table. (unit: name) |
| event_root | string | CAMEO root event code (2 digits, 01-20); primary key together with date and country_code. '14' = Protest, '18' = Assault, '19' = Fight, '20' = Use unconventional mass violence. (unit: CAMEO root code) |
| event_root_label | string | Human label for event_root from the GDELT 2.1 codebook, e.g. 'Engage in diplomatic cooperation'. (unit: label) |
| n_events | integer | Number of GDELT root events (IsRootEvent=1, GLOBALEVENTID-deduped) in this (country, root) cell. Cells below 3 events are gated out. (unit: events) |
| event_share_pct | float | The cell's share of the country's daily root events (n_events / country_event_count * 100), 0-100. Sums to <= 100 across the country's cells because sub-threshold cells are gated out. (unit: percent) |
| total_articles | integer | Sum of GDELT NumArticles across the cell's events — a coverage-breadth amplifier: high values mean many outlets carried the events. (unit: articles) |
| mean_tone | float | Mean GDELT AvgTone (-100 very negative to +100 very positive) across the cell's events. AvgTone is a dictionary measure of sentiment, not sentiment itself. (unit: -100..100) |
| pct_negative_tone | float | Share of the cell's events with AvgTone < 0, 0-100. (unit: percent) |
| mean_goldstein | float | Mean GDELT GoldsteinScale (-10 conflict to +10 cooperation) across the cell's events. (unit: -10..10) |
| pct_conflict_events | float | Share of the cell's events with QuadClass 3 (verbal conflict) or 4 (material conflict), 0-100. Events with an invalid QuadClass are excluded from numerator and denominator. (unit: percent) |
| pct_cooperation_events | float | Share of the cell's events with QuadClass 1 (verbal cooperation) or 2 (material cooperation), 0-100. Invalid QuadClass rows are excluded from numerator and denominator. (unit: percent) |
| mix_concentration | float | 0-100 Herfindahl concentration of the country's daily root-event mix: 100 * sum over kept cells of (cell share)^2. 100 = every event in one category; lower = more diverse coverage. (unit: score 0-100) |
| root_rank | integer | Rank of the cell within (date, country): 1 = most events. Ties broken by total_articles desc, then event_root asc. (unit: rank) |
| country_event_count | integer | The country's total daily root events (denominator for event_share_pct). Countries below 5 daily events are gated out. (unit: events) |
| day_root_count | integer | Global daily root-event count in this root category across all gated countries — the day's worldwide volume for the category. (unit: events) |
First 10 sample rows — a preview, not the complete dataset.
| date | as_of | fetched_at | country_code | country_name | event_root | event_root_label | n_events | event_share_pct | total_articles | mean_tone | pct_negative_tone | mean_goldstein | pct_conflict_events | pct_cooperation_events | mix_concentration | root_rank | country_event_count | day_root_count |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2026-09-26 | 2026-09-26 | 2026-09-26T00:00:00+0000 | AFG | Afghanistan | 04 | Consult | 30 | 25.86 | 146 | -5.14 | 86.67 | 2.88 | 0 | 100 | 15.91 | 1 | 116 | 10,688 |
| 2026-09-26 | 2026-09-26 | 2026-09-26T00:00:00+0000 | AFG | Afghanistan | 19 | Fight | 23 | 19.83 | 86 | -7.9 | 91.3 | -10 | 100 | 0 | 15.91 | 2 | 116 | 1,972 |
| 2026-09-26 | 2026-09-26 | 2026-09-26T00:00:00+0000 | AFG | Afghanistan | 01 | Make public statement | 22 | 18.97 | 98 | -3.27 | 72.73 | -0.4 | 0 | 100 | 15.91 | 3 | 116 | 4,848 |
| 2026-09-26 | 2026-09-26 | 2026-09-26T00:00:00+0000 | AFG | Afghanistan | 17 | Coerce | 10 | 8.62 | 25 | -5.21 | 100 | -5 | 100 | 0 | 15.91 | 4 | 116 | 1,630 |
| 2026-09-26 | 2026-09-26 | 2026-09-26T00:00:00+0000 | AFG | Afghanistan | 02 | Appeal | 7 | 6.03 | 22 | -1.26 | 57.14 | 3 | 0 | 100 | 15.91 | 5 | 116 | 2,517 |
| 2026-09-26 | 2026-09-26 | 2026-09-26T00:00:00+0000 | AFG | Afghanistan | 18 | Assault | 6 | 5.17 | 19 | -8.69 | 100 | -9.67 | 100 | 0 | 15.91 | 6 | 116 | 439 |
| 2026-09-26 | 2026-09-26 | 2026-09-26T00:00:00+0000 | AFG | Afghanistan | 12 | Reject | 5 | 4.31 | 25 | -6.8 | 100 | -4 | 100 | 0 | 15.91 | 7 | 116 | 962 |
| 2026-09-26 | 2026-09-26 | 2026-09-26T00:00:00+0000 | AFG | Afghanistan | 11 | Disapprove | 3 | 2.59 | 18 | -8.59 | 100 | -2 | 100 | 0 | 15.91 | 8 | 116 | 2,090 |
| 2026-09-26 | 2026-09-26 | 2026-09-26T00:00:00+0000 | AFG | Afghanistan | 05 | Engage in diplomatic cooperation | 3 | 2.59 | 14 | 0.34 | 33.33 | 3.43 | 0 | 100 | 15.91 | 9 | 116 | 3,122 |
| 2026-09-26 | 2026-09-26 | 2026-09-26T00:00:00+0000 | AGO | Angola | 04 | Consult | 28 | 84.85 | 112 | 6.93 | 0 | 5 | 0 | 100 | 74.29 | 1 | 33 | 10,688 |
- Current
20260927T231515Z-61e9775ca1f7 · sha256 61e9775ca1f7…
1,069 rows · first snapshot
Point any LLM at the metadata endpoint — the documentation above is machine-readable too (JSON-LD + Croissant).
curl "https://datazimuts.com/v1/datasets/gdelt_news_signals/gdelt_event_roots_daily" | jq '{title, rows, columns_count, license}'import requests
ds = requests.get("https://datazimuts.com/v1/datasets/gdelt_news_signals/gdelt_event_roots_daily").json()
print(ds["title"], ds["rows"], "rows")
# Sample rows for an LLM context window
for row in ds.get("sample_rows", [])[:5]:
print(row)API endpoint: https://datazimuts.com/v1/datasets/gdelt_news_signals/gdelt_event_roots_daily
Tip: fetch /llms.txt for the full machine-readable catalog.
Where this data comes from and what was made from it. Other people's work shows as counts; only shared projects are named.
Cite this snapshot
Pinned to snapshot 20260927T231515Z-61e9775ca1f7 and its content hash, so readers get exactly the data you used.
GDELT global news attention & tone intelligence. (2026). GDELT daily event-roots mix by country [Data set, snapshot 20260927T231515Z-61e9775ca1f7, sha256 61e9775ca1f7]. Datazimuts. Retrieved 2026-09-28, from https://datazimuts.com/en/datasets/gdelt_news_signals/gdelt_event_roots_daily?snapshot=20260927T231515Z-61e9775ca1f7
@misc{dz_gdelt_news_signals_gdelt_event_roots_dai_61e9775c,
title = {{GDELT daily event-roots mix by country}},
author = {{GDELT global news attention \& tone intelligence}},
year = {2026},
publisher = {Datazimuts},
howpublished = {\url{https://datazimuts.com/en/datasets/gdelt_news_signals/gdelt_event_roots_daily?snapshot=20260927T231515Z-61e9775ca1f7}},
note = {Snapshot 20260927T231515Z-61e9775ca1f7, sha256 61e9775ca1f7637fc6e8cc75f79fa97009f0ce39c5ba65e9b7b77ddd37504ff4; accessed 2026-09-28}
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