# Global News Scraper: Worldwide News with Sentiment (GDELT) (`richiedc95/global-news-scraper`) Actor

Monitor online news worldwide in 65+ languages, updated every 15 minutes: title, URL, outlet, language, sentiment (tone), people, organizations and places for each article. Keyword, country, language, site and tone filters. No blocking.

- **URL**: https://apify.com/richiedc95/global-news-scraper.md
- **Developed by:** [Richie Data](https://apify.com/richiedc95) (community)
- **Categories:** News, Marketing, AI
- **Security:** Limited permissions
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $1.60 / 1,000 articles

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## 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**.

⭐ **Is this Actor useful to you?** A short review on the Reviews tab helps other users find it, and tells us what to build next.

- 🌍 **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

```json
{
    "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](https://www.gdeltproject.org/), 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**

```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**

```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](https://mcp.apify.com) 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](https://github.com/richiedc95/job-search-mcp/blob/main/examples/README.md).
- 📥 **Exports**: download every run as JSON, CSV, Excel, XML or RSS, or read it through the [Apify API](https://docs.apify.com/api/v2).

### 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:

```text
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.

### Related Actors

- [Public Tenders Scraper (UK, EU, Canada, Colombia)](https://apify.com/richiedc95/public-tenders-scraper)
- [Job Search Scraper: 25,500+ Company Career Sites](https://apify.com/richiedc95/company-jobs-search)
- [Career Site Jobs Scraper (any ATS)](https://apify.com/richiedc95/career-site-jobs-scraper)

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

# Actor input Schema

## `queries` (type: `array`):

One query per line, matched against the headline, URL and the people, organizations and names found in the article (case- and accent-insensitive). All words must appear; use "exact phrases", OR between alternatives and -word to exclude. Leave empty to get every article that passes the filters.

## `publishedWithin` (type: `string`):

How far back to read. Each 15 minutes of worldwide news (about 2,500 articles) costs $0.002 to scan, so 24 hours cost about $0.19 plus the articles saved. For alerts, schedule short windows (e.g. every hour with "Last hour").

## `languages` (type: `array`):

Keep only articles written in these languages, by English name: English, Spanish, French, German, Portuguese, Chinese, Russian, Arabic... Empty = all 65+ languages.

## `countries` (type: `array`):

Keep only articles that mention places in these countries, by English name: United States, Peru, Germany, India...

## `domains` (type: `array`):

Keep only articles from these domains (subdomains included), e.g. reuters.com, bbc.co.uk.

## `excludeDomains` (type: `array`):

Skip articles from these domains.

## `minTone` (type: `integer`):

Keep only articles with a tone (sentiment) of at least this value. Typical range -10 (very negative) to +10 (very positive).

## `maxTone` (type: `integer`):

Keep only articles with a tone of at most this value, e.g. -3 for clearly negative coverage (adverse media).

## `includeThemes` (type: `boolean`):

Add the list of GDELT themes detected in each article (topics such as ELECTION, PROTEST, ECON_INFLATION).

## `removeDuplicateTitles` (type: `boolean`):

Keep only the first article for each headline. Wire stories are republished by many outlets; turn this off to count every mention.

## `onlyNewArticles` (type: `boolean`):

Return only articles not returned in previous runs. Schedule it every hour or every day for a media-monitoring feed.

## `maxItemsPerQuery` (type: `integer`):

Stop collecting a query after this many articles. 0 = no limit.

## `maxItems` (type: `integer`):

Stop the run after this many articles. 0 = no limit.

## Actor input object example

```json
{
  "queries": [
    "\"artificial intelligence\"",
    "tesla OR rivian"
  ],
  "publishedWithin": "3h",
  "includeThemes": false,
  "removeDuplicateTitles": false,
  "onlyNewArticles": false,
  "maxItemsPerQuery": 100,
  "maxItems": 0
}
```

# Actor output Schema

## `articles` (type: `string`):

No description

## `summary` (type: `string`):

No description

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "queries": [
        "\"artificial intelligence\"",
        "tesla OR rivian"
    ],
    "publishedWithin": "3h",
    "maxItemsPerQuery": 100
};

// Run the Actor and wait for it to finish
const run = await client.actor("richiedc95/global-news-scraper").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "queries": [
        "\"artificial intelligence\"",
        "tesla OR rivian",
    ],
    "publishedWithin": "3h",
    "maxItemsPerQuery": 100,
}

# Run the Actor and wait for it to finish
run = client.actor("richiedc95/global-news-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "queries": [
    "\\"artificial intelligence\\"",
    "tesla OR rivian"
  ],
  "publishedWithin": "3h",
  "maxItemsPerQuery": 100
}' |
apify call richiedc95/global-news-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,richiedc95/global-news-scraper"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/5TSYdoMvah2GCxp6E/builds/17OE1KwLvaD6IqJEF/openapi.json