News API & Scraper: Worldwide News with Sentiment (GDELT)

Get online news from all over the world, updated every 15 minutes, as clean structured data: headline, URL, outlet, language, sentiment (tone), and the people, organizations and places mentioned in each article. It reads the full worldwide news stream processed by the GDELT Project: roughly 250,000 articles a day in 65+ languages.

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• 🌍 Worldwide, multilingual: national, regional and local outlets in every country, not only English-language sites.
• 🧠 Entities and sentiment included: people, organizations, countries, places and a tone score for every article.
• 🔎 Cross-language search: a query like tesla also finds articles in Chinese or Spanish that mention Tesla, because it matches the names detected in the article, not only the headline.
• 🎯 Filters: language, mentioned countries, sites, and tone (for example only negative coverage for adverse-media checks).
• 🔔 Monitoring mode: schedule it and receive only articles you have not seen before.
• ⚡ Fast and reliable: no search-engine pages, no CAPTCHAs, no rate limits. A 3-hour window takes seconds.

Who uses it

• PR and communications teams tracking mentions of a brand, product or executive in any language.
• Risk, compliance and KYC teams screening adverse media about companies or people (filter by negative tone).
• Market and competitive intelligence: news about competitors, suppliers, countries or sectors.
• Traders and analysts following the news flow and sentiment about companies, commodities or countries.
• Researchers and journalists studying coverage across countries and languages.
• AI agents and RAG pipelines that need fresh, structured news with entities.

How to use it

1. Add search queries (for example "electric vehicles", tesla OR rivian, openai -sports), or leave them empty and use only filters.
2. Choose how far back to read (Published within) and, optionally, languages, countries, sites or a tone range.
3. Click Start. For alerts, turn on Only new articles and schedule the Actor (for example every hour with "Last hour").

Example input

{
    "queries": ["\"lithium mining\"", "codelco OR sqm"],
    "publishedWithin": "24h",
    "countries": ["Chile", "Peru", "Argentina"],
    "maxTone": -2,
    "removeDuplicateTitles": true
}

Output

Field	Description
publishedAt	When GDELT saw the article (15-minute precision, UTC)
title	Headline in its original language
url, domain	Article link and news outlet
language	Language of the article
tone, positiveScore, negativeScore	Sentiment: average tone (negative = negative coverage) and its positive/negative components
wordCount	Length of the article
persons, organizations	People and organizations mentioned
mentionedCountries, locations	Countries and places mentioned
themes	Optional: GDELT topics detected (elections, protests, inflation...)
imageUrl	Main image of the article
query	The query that matched
source	Data attribution: GDELT Project

The SUMMARY record shows how many articles were scanned and saved, per query.

Pricing

• $2.00 per 1,000 articles saved.
• $0.002 per 15 minutes of news scanned (about 2,500 articles read from GDELT's files): $0.008 for 1 hour, $0.19 for 24 hours.

Hourly monitoring of a brand costs a few cents a day. Use Max articles to cap a run.

FAQ

Where does the data come from? From the GDELT Project, an open index of worldwide online news that is free for any use, including commercial use. Every item cites GDELT, as GDELT asks.

Does it return the full article text? No. It returns the headline, link, outlet, language, sentiment, entities and image. The text belongs to each publisher; follow the URL to read it.

How fresh is it? GDELT publishes a new batch every 15 minutes, usually less than an hour after publication. Occasionally a batch is late; the run summary lists missing batches.

How far back can I go? Up to 72 hours per run. For a longer archive, schedule the Actor daily and keep the datasets.

Why does a query match an article whose headline does not contain the word? Queries also match the people, organizations and names detected in the article, which finds coverage in other languages. Use "exact phrases" or exclusions to narrow it.

Use it from your code, AI agents and automations

Python

from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_TOKEN>")
run = client.actor("richiedc95/global-news-scraper").call(run_input={
    "queries": [
        "\"artificial intelligence\"",
        "tesla OR rivian"
    ],
    "publishedWithin": "24h",
    "onlyNewArticles": True
})
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

JavaScript

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: '<YOUR_APIFY_TOKEN>' });
const run = await client.actor('richiedc95/global-news-scraper').call({
    "queries": [
        "\"artificial intelligence\"",
        "tesla OR rivian"
    ],
    "publishedWithin": "24h",
    "onlyNewArticles": true
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();

• 🤖 AI agents (MCP): add the Apify MCP server to Claude, ChatGPT, Cursor or any MCP client and this Actor becomes a tool your agent can call.
• 🔗 No-code (n8n, Make, Zapier): one HTTP request runs the Actor and returns the results, so any automation tool can use it. In n8n, add an HTTP Request node with method POST, URL https://api.apify.com/v2/acts/richiedc95~global-news-scraper/run-sync-get-dataset-items?token=<YOUR_APIFY_TOKEN> and the JSON input above as the body, then send the items to Slack, Google Sheets, email or a CRM. Put a Schedule node in front for daily alerts. Make and Zapier have official Apify apps (Run an Actor → Get dataset items). Ready-made n8n workflows (import from URL) and a step-by-step guide: n8n / Make / Zapier examples.
• 📥 Exports: download every run as JSON, CSV, Excel, XML or RSS, or read it through the Apify API.

Get a fresh feed automatically (news alerts, dashboards, media monitoring)

1. Click Save as a new task with your input (turn on the monitoring option if the Actor has one, so each run returns only new articles).
2. Add a schedule to the task (hourly, daily or weekly) under Schedules.
3. Read the latest results from one stable URL, in the format your tool expects:

https://api.apify.com/v2/actor-tasks/<TASK_ID>/runs/last/dataset/items?token=<YOUR_APIFY_TOKEN>&status=SUCCEEDED&format=csv

Use format=json, csv, xlsx, xml or rss. RSS readers, Slack bots and spreadsheets can import that URL directly.

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Found a bug or need a feature? Open an issue on the Issues tab and we will usually answer within a day.