France 24 runs four desks on one host - French, English, Arabic and Spanish - each with its own sections and tags. We collect their articles, videos, shows and Newsfeed into one schema.
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ScrapeIt runs France 24 data scraping as a managed service: we build the collector, host it and repair it when templates change. New items are found through the news sitemaps and monthly sitemaps, and fields are read from the pages themselves. The service includes anti-bot handling, proxy rotation and CAPTCHA solving, since france24.com screens automated clients at the edge. Nothing on the site needs a login. Rows carry desk, language and collection time, and arrive as CSV, JSON or XLSX in S3, SFTP or your warehouse, or through a France 24 scraper API endpoint we host.
Article, video and show pages carry NewsArticle or VideoObject markup, and editorial pages add an analytics data layer; together they give a record without parsing the layout. To extract France 24 data cleanly we keep these fields:
Sponsored content is kept apart: it sits under /en/sponsored-content/, its articleSection reads Sponsored content and the sponsor is credited as author.
France 24 is a television channel first, so many records are video.
We keep media as metadata and links; the footage stays with FMM.
A France 24 scraper has to treat one domain as four newsrooms. France 24, the international news channel of France Medias Monde, went on air on 6 December 2006 in French and English, added Arabic in April 2007 and a Spanish service in 2017. All four live on www.france24.com as path prefixes: /fr/, /en/, /ar/ and /es/. France 24 is free to read and watch, with no paywall, no meter and no registration wall, so every article renders in full.
What the desks share is the frame. The four fronts point to each other with hreflang, show brands such as Focus, Reporters and The Observers run in several languages, and one CMS builds every page with the same markup. What they write separately is the journalism. Articles carry no hreflang to a counterpart, each desk tags with its own taxonomy (the tag Israel has one ID in English and another in Spanish), and the section trees differ: the Spanish desk splits America Latina from the US and Canada, France 24 Arabic runs a Maghreb section, the English desk a single Americas section.
Addresses follow the language. French and Spanish slugs keep their accents, Arabic slugs are written in Arabic script and arrive percent-encoded, and inLanguage reads fr, en, ar or es-419, since the Spanish service writes for Latin America. The section in an article URL is not always the slug of the section page, so sections are read from the markup, not from the path.
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France 24 was built to carry a French perspective on world affairs, and each of its four desks chooses what its own audience hears. One company, one CMS and one data layer sit behind all four, so differences between desks are editorial, not technical.
Learn how to use web scraping to solve data problems for your organization
Leveraging advances in technology, the AI-powered web scraper has skyrocketed in demand and is helping to expand capabilities by automating tedious daily tasks and speeding up data collection from thousands of websites several times over.
Web scraping is a method of obtaining web data by extracting it from pages of web resources with the help of a program, that is, in automatic mode. It is used to syntactically convert web pages into more usable forms.
If you specialize in machine learning, you need to feed large amounts of data to the algorithms. Web scraping is the easiest and the most efficient method of collecting the data from all over the Internet.
ScrapeIt is a managed web scraping agency. You name the desks, sections, shows and date range; we design the crawl, run it and deliver records that load without cleaning. A sample comes first, usually a week of two desks with IDs, tags and credits, so you can test the schema before a schedule is agreed. The price of a France 24 dataset depends on languages, content types, refresh rate and archive depth, from a five-minute headline monitor to a one-off pull back to 2006.
Yes. The ScrapeIt France 24 API returns the content ID, headline, standfirst, dates, tags and credits for all four desks as JSON from an endpoint we host, refreshed on the schedule you set. The same data also comes as CSV or XLSX files or straight into your database.
Within minutes. A five-minute headline monitor polls the fronts of France 24 English, French, Arabic and Spanish, the Newsfeed and the news sitemaps, and reads each new page once. Each record comes with headline, standfirst, section, tags, credits, datePublished and dateModified, and the full text.
To the launch. Month pages under /en/archives/, /fr/archives/ and their Spanish and Arabic twins list articles, shows and videos by day, filter by section and page through the month, so France 24 archives 2025 means twelve monthly listings per desk. Monthly sitemaps start in late 2006 for English and French, May 2007 for Arabic and April 2017 for Spanish. Addresses changed over time: 2007 stories sit at /en/YYYYMMDD-slug with no section, today's at /en/section/YYYYMMDD-slug, and some video and fact-check pages use a bare slug with no date.
Yes, as a derived link rather than a declared one. France 24 articles carry no hreflang to their counterparts, tag IDs differ between desks and slugs are written in each language, so versions are matched on publication time, named entities and shared agency pictures. Each match comes with a confidence score, and you can keep only the certain ones or review the rest. Unmatched stories stay in the data, which is how you see what one desk covered and the others skipped.
Yes. We collect only publicly available data - everything a visitor sees on France 24, the France Medias Monde news channel - and we collect it legally. Across all four desks that means articles with headline, standfirst, full text, dates, section, tags and credits, plus videos, shows and the Newsfeed, all without a login or any special access. Observers' contributors are private people and stay out.
Step 1 - Make a Request
You share your needs, expectations, and desired timeframe. We’ll suggest the best solution based on your request and budget.
Step 2 - Configuring Custom Web Crawlers
Our specialists configure the crawlers and extract a sample dataset for your review before proceeding with the full-scale extraction.
Step 3 - Collect and Deliver
Once you approve the sample, we launch the project and start full data collection. We gather, filter, and structure the data for easy use, delivering it on time in your preferred format.
Step 4 - Maintain and Support
Our team manages ongoing processes, monitors website changes, and supports all data extraction cycles. We can also help integrate data into your systems or create dashboards to simplify analysis.
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