# Track Company News By Name Or Ticker

**Use case:** 

One search term per company, run in parallel, with the date window as wide as you need. Set a minimum on how many outlets covered the same story and you get a cheap relevance signal: Google groups coverage and lists the other outlets inside the feed entry.

## Input

```json
{
  "queries": [
    "\"Tesla\"",
    "\"Nvidia\"",
    "\"Apple Inc\""
  ],
  "topics": [],
  "topicUrls": [],
  "geoLocations": [],
  "includeTopStories": false,
  "edition": "US:en",
  "daysBack": 14,
  "breakFeedCap": true,
  "resolveArticleUrls": true,
  "fetchArticleMeta": false,
  "maxItems": 800,
  "onlyNew": false,
  "emitUnchanged": false,
  "titleContains": [],
  "excludeKeywords": [],
  "publishers": [],
  "excludePublishers": [],
  "publishedWithinHours": 0,
  "withUrlOnly": false,
  "minRelatedArticles": 2,
  "includeRelatedArticles": true,
  "compactOutput": false,
  "excludeEmptyFields": false
}
```

## Output

```json
{
  "title": {
    "label": "Headline",
    "format": "string"
  },
  "publisher": {
    "label": "Publisher",
    "format": "string"
  },
  "publisher_domain": {
    "label": "Domain",
    "format": "string"
  },
  "url": {
    "label": "Article URL",
    "format": "string"
  },
  "published_at": {
    "label": "Published",
    "format": "string"
  },
  "snippet": {
    "label": "Snippet",
    "format": "string"
  },
  "description": {
    "label": "Article description",
    "format": "string"
  },
  "image": {
    "label": "Image",
    "format": "string"
  },
  "related_count": {
    "label": "Other outlets",
    "format": "integer"
  },
  "source_type": {
    "label": "Found by",
    "format": "string"
  },
  "query": {
    "label": "Search term",
    "format": "string"
  },
  "topic": {
    "label": "Topic",
    "format": "string"
  },
  "geo": {
    "label": "City",
    "format": "string"
  },
  "geo_fallback": {
    "label": "City not recognised",
    "format": "boolean"
  },
  "edition": {
    "label": "Edition",
    "format": "string"
  },
  "country": {
    "label": "Country",
    "format": "string"
  },
  "language": {
    "label": "Language",
    "format": "string"
  },
  "change_type": {
    "label": "Change",
    "format": "string"
  },
  "url_resolved": {
    "label": "URL resolved",
    "format": "boolean"
  },
  "google_news_url": {
    "label": "Google News link",
    "format": "string"
  },
  "publisher_url": {
    "label": "Publisher home",
    "format": "string"
  },
  "published_timestamp": {
    "label": "Published (unix)",
    "format": "integer"
  },
  "title_raw": {
    "label": "Headline as published",
    "format": "string"
  },
  "related": {
    "label": "Related coverage",
    "format": "array"
  },
  "article_id": {
    "label": "Article id",
    "format": "string"
  },
  "scraped_at": {
    "label": "Collected at",
    "format": "string"
  }
}
```

## About this Actor

This example demonstrates how to use [Google News Media Monitoring Scraper - Brand Mention Monitor](https://apify.com/snow_leo_data/google-news-scraper.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/snow_leo_data/google-news-scraper.md) to learn more, explore other use cases, and run it yourself.


## How to integrate an Actor?

This Task's input is already configured above. Use it as-is rather than inventing a new one.

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 full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/snow_leo_data/google-news-scraper.md

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`).