Ars Technica Rss Scraper

Ars Technica RSS Scraper — Collect Technology News, Headlines, and Story Metadata

Overview

Ars Technica RSS Scraper collects recent story listings from supported Ars Technica feeds and organizes them into structured dataset records. Each record can include the headline, story link, publication date, author, categories, comment count, short summary, image link, and unique story identifier.

Designed for technology news monitoring, topic research, and content analysis, the scraper supports JSON, CSV, and Excel exports. Schedule regular runs to build an ongoing collection of recent stories.

Features

• Story collection: Collect recent stories from supported Ars Technica news and technology-lab feeds.
• Keyword filtering: Filter stories by keywords in headlines and short summaries.
• Metadata extraction: Collect publication dates, authors, categories, comment counts, and image links when available.
• Plain-text summaries: Convert HTML-formatted summaries into readable text.
• Summary length control: Limit summaries to 500 characters.
• Duplicate detection: Use guid identifiers to identify and skip duplicate stories.
• Structured exports: Export collected records to JSON, CSV, or Excel.
• Lightweight collection: Collect story listings and summaries without storing full article bodies.

Use Cases

Technology News Monitoring

Track recent headlines and developments across technology topics and industry trends.

Section Monitoring

Collect stories from supported technology-lab and general news feeds to organize different areas of coverage.

Keyword Research

Find stories mentioning specific companies, products, technologies, or industry developments.

Research and Reporting

Organize headlines, publication dates, authors, categories, and summaries for research and reporting workflows.

Content Analysis

Review story categories, recurring topics, and publication patterns over time.

Data Processing

Export structured news records for filtering, sorting, analysis, and further processing.

Input Parameters

Parameter	Type	Default	Description
feedUrls	Array	Index and technology-lab feeds	List of supported Ars Technica feed locations. Only supported feed hosts are accepted.
keyword	String	Empty	Optional keyword filter applied to headlines and short summaries.
maxItems	Integer	100	Maximum number of stories to save, from 1 to 1,000.
timeoutSecs	Integer	300	Maximum run duration in seconds.
requestTimeoutSecs	Integer	30	Maximum wait time for an individual feed download, in seconds.

Example Input

This configuration collects up to 100 stories matching the keyword technology from two supported feeds.

{
  "feedUrls": [
    "FEED_URL_1",
    "FEED_URL_2"
  ],
  "keyword": "technology",
  "maxItems": 100,
  "timeoutSecs": 300,
  "requestTimeoutSecs": 30
}

Use supported Ars Technica feed locations for feedUrls. Unsupported feed locations are not processed.

Extracted Data

Each successfully collected story is saved as a structured dataset record.

Field	Type	Description
itemTitle	String	Story headline provided by the feed.
link	String	Link to the original story.
comments	String	Comment count, when available.
author	String	Story author, when provided.
pubDate	String	Publication date supplied by the feed.
categories	Array	Categories or tags associated with the story.
guid	String	Unique story identifier used to identify duplicate records.
summary	String	Plain-text story summary, limited to 500 characters.
imageUrl	String	Story image link, when available.
scrapedAt	String	UTC timestamp indicating when the record was collected.

The fields itemTitle and summary are used instead of title and description to avoid conflicts with reserved dataset schema field names.

The scraper collects story listings and summaries rather than the full article body.

Example Output

{
  "itemTitle": "Example technology headline",
  "link": "ARTICLE_URL",
  "comments": "29",
  "author": "Example Author",
  "pubDate": "Sun, 11 Oct 2026 14:50:24 +0000",
  "categories": [
    "Technology",
    "News"
  ],
  "guid": "STORY_UNIQUE_IDENTIFIER",
  "summary": "A short summary of the story.",
  "imageUrl": "IMAGE_URL",
  "scrapedAt": "2026-10-12T00:00:00+00:00"
}

This example illustrates the output structure. Actual values depend on the feed items available during collection and the configured keyword filter.

Working with Your Dataset

Choose an export format according to your workflow:

• JSON: Suitable for structured data processing and application workflows.
• CSV: Convenient for spreadsheet analysis, filtering, and sorting.
• Excel: Useful for reporting, reviewing story metadata, and sharing research with a team.

For ongoing monitoring, schedule regular runs and use guid to identify stories already collected. RSS feeds generally provide recent items rather than a complete historical archive, so maintaining your own dataset helps preserve records over time.

Important Notes

• Only supported Ars Technica feed locations are processed.
• Keyword filtering applies to headlines and short summaries.
• Summary text is limited to 500 characters.
• Some fields, including author, comment count, categories, and image links, may be unavailable for individual stories.
• The scraper collects story listings and summaries, not full article bodies.
• Results depend on the items available in the selected feeds at collection time.

FAQ

Can I collect stories from multiple feeds in one run?

Yes. Provide multiple supported feed locations in the feedUrls array.

Can I filter stories by keyword?

Yes. Set keyword to the term you want to find in headlines and short summaries. Leave it empty to collect stories without a keyword filter.

How many stories can one run collect?

The default limit is 100 stories. You can increase maxItems to a maximum of 1,000.

Does the scraper collect full articles?

No. It collects story listings, metadata, and short summaries rather than full article bodies.

Why might some fields be empty or missing?

Not every feed item includes all metadata. Author names, comment counts, categories, and image links depend on the information available for each story.

What export formats are supported?

You can export the dataset as JSON, CSV, or Excel.

How can I maintain a collection of stories over time?

Schedule regular runs and retain your dataset between collections. Use guid to help identify previously collected stories and avoid duplicates.

Disclaimer

This Actor is an independent tool and is not affiliated with, endorsed by, sponsored by, or otherwise officially associated with Ars Technica or its owners. Users are responsible for complying with applicable source terms and collection restrictions.

Is Web Scraping Legal?

Collecting information that is already public is generally legal. Scraping is not the same thing as hacking, and there is no single law that bans it. The limits are the usual ones: do not break into accounts, do not take private or confidential data, and be careful with personal data and copyrighted works. A site's terms can also restrict how you access it. Facts such as a public name, price, or rating are not the same thing as republishing someone's article or photo.

This actor collects information from public pages. It does not log in and it does not bypass access controls.

For a longer explanation, see Apify's article Is web scraping legal?.