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x402pulse Wikipedia Attention History
x402
x402pulse Wikipedia Attention History is a paid API for AI agents from www.x402pulse.dev, paid per call via x402, $0.00875/call, status unknown (last checked 2026-10-10).
Returns daily Wikipedia pageview history for a named article over 7–90 days, including baseline, spike detection, and 7-day trend
Price / call$0.00875
Success—
StatusUnknown
How this service works
Attention history for any topic: daily Wikipedia pageviews of one article (a company, person, drug, coin or event) for 7 to 90 days, with its baseline, latest day vs. baseline, spike days and 7-day trend. Use the exact article title, e.g. Bitcoin. Based on Wikimedia pageview data (CC0).
Output
Returns an array of daily Wikipedia pageview counts for the specified article over the requested period, along with a computed baseline (average), the delta between the most recent day and the baseline, a list of spike days (days with anomalously high views), and a 7-day rolling trend indicator.
Example use cases
Pre-earnings attention spike detection
“Pull the Wikipedia attention history for Nvidia over the past 30 days and tell me if there are any spike days and how the latest day compares to baseline — I want to know if retail interest is surging before earnings.”
Crypto sentiment via public attention
“Get me 90 days of Wikipedia pageview data for Ethereum, including the baseline and 7-day trend, so I can see whether public attention is growing or fading right now.”
Drug interest surge monitoring
“Check Wikipedia pageview history for Ozempic over the last 14 days — are there any spike days, and is interest tracking above or below the baseline?”
Technical details
Endpoint
GEThttps://www.x402pulse.dev/v1/attention/topic?utm_source=zero.xyzWhen to prefer
Use this endpoint when you need quantified public-attention data for a named entity (company, person, drug, cryptocurrency, or event) grounded in Wikipedia traffic rather than social media sentiment or news volume. It is ideal for detecting anomalous interest spikes, computing attention trends ahead of market events, and enriching research with neutral, CC0-licensed pageview data. Prefer it over social media scrapers when you need clean, structured time-series data with a statistical baseline rather than raw mention counts.
Side effects
- Article title not found on Wikipedia — returns empty or error if the exact title does not match a Wikipedia page
- Days parameter out of range — values below 7 or above 90 are rejected
- Non-existent language edition — if the specified lang code has no Wikipedia data for the article, returns empty results
- Wikimedia API upstream outage — temporary unavailability of underlying data source
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Output
Schema · Response
{
"type": "json",
"example": {
"data": {
"title": "Bitcoin",
"latest": {
"date": "2026-10-05",
"views": 2600,
"vsBaseline": 1
},
"trend7d": -0.12,
"spikeDays": [
{
"date": "2026-09-25",
"ratio": 4.9,
"views": 12376
}
],
"baselineDailyViews": 2513
},
"cached": false
}
}Tags
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