Wikipedia economic-attention & fear signals
Monthly revealed-attention signals from English-Wikipedia pageviews (2015 ->): attention paid to economically revealing articles (Recession, Inflation, Unemployment, Great Recession, Stock market crash, Layoff), with 3-month momentum, 12-month change volatility, 3-sigma anomaly flags, drift forecasts, 5-year attention z-scores, attention-spike flags, and a composite economic-fear index (cross-article mean z-score) with high/extreme fear flags. The revealed-attention companion to us-consumer-sentiment-signals (stated sentiment) and crypto-fear-greed-signals (market-implied fear). All rows normalized to country_code WLD (global internet attention). Raw data: Wikimedia Foundation pageview statistics API.
Quality
Attribution
Wikimedia Foundation pageview statistics; derived signals by Frontier Data Hub
Schema
| Column | Type | Description |
|---|---|---|
| date | string | Month of observation (Wikimedia pageviews API timestamp, YYYY-MM-DD with day fixed to 01, monthly granularity). |
| country | string | |
| country_code | string | |
| series_id | string | WIKI_<ARTICLE> for the six tracked articles, or FEAR_INDEX for the composite economic-fear index. |
| series_label | string | Article tracked, e.g. 'Wikipedia pageviews: Recession (monthly)'; the composite is labeled as the cross-article mean of 5-year z-scored pageviews. |
| value | float | Monthly pageview count for the article on English Wikipedia (Wikimedia pageviews API, all-access, all-agents); for FEAR_INDEX, the cross-article mean of 5-year z-scored pageviews (index points). |
| momentum_3m | float | |
| volatility_30d | float | |
| anomaly_flag | integer | |
| forecast_1m | float | |
| views_z_5y | float | |
| spike_flag | integer | |
| high_fear_flag | integer | |
| extreme_fear_flag | integer |
Sample rows
| date | country | country_code | series_id | series_label | value | momentum_3m | volatility_30d | anomaly_flag | forecast_1m | views_z_5y | spike_flag | high_fear_flag | extreme_fear_flag |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2020-06-01 | World | WLD | FEAR_INDEX | Economic fear index: cross-article mean of 5-year z-scored Wikipedia pageviews | -0.5031571352880647 | — | — | 0 | — | -0.5031571352880647 | 0 | 0 | 0 |
| 2020-07-01 | World | WLD | FEAR_INDEX | Economic fear index: cross-article mean of 5-year z-scored Wikipedia pageviews | -0.8433255005830086 | — | — | 0 | — | -0.8433255005830086 | 0 | 0 | 0 |
| 2020-08-01 | World | WLD | FEAR_INDEX | Economic fear index: cross-article mean of 5-year z-scored Wikipedia pageviews | -0.6294864317914918 | — | — | 0 | — | -0.6294864317914918 | 0 | 0 | 0 |
| 2020-09-01 | World | WLD | FEAR_INDEX | Economic fear index: cross-article mean of 5-year z-scored Wikipedia pageviews | -0.7042763188508934 | -0.20111918356282865 | — | 0 | — | -0.7042763188508934 | 0 | 0 | 0 |
| 2020-10-01 | World | WLD | FEAR_INDEX | Economic fear index: cross-article mean of 5-year z-scored Wikipedia pageviews | -0.537464891711686 | 0.3058606088713226 | — | 0 | — | -0.537464891711686 | 0 | 0 | 0 |
Download sample data
Download the full sample snapshot for this dataset (sample rows, not the complete dataset).
Use with an LLM
Point any LLM at the metadata endpoint — the documentation above is machine-readable too (JSON-LD + Croissant).
cURL
curl "https://datazimuts.com/v1/datasets/wiki_attention_signals/wiki_economic_attention_signals" | jq '{title, rows, columns_count, license}'Python
import requests
ds = requests.get("https://datazimuts.com/v1/datasets/wiki_attention_signals/wiki_economic_attention_signals").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/wiki_attention_signals/wiki_economic_attention_signals
Tip: fetch /llms.txt for the full machine-readable catalog.