We extract article text, author profiles, Explainer series, and metadata from Vox. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your schedule.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Articles objects from vox.com. All fields typed and schema-versioned.
"url": "https://www.vox.com/technology/2026/article-slug", "headline": "The future of generative models", "author": "Kelsey Piper", "publish_date": "2026-05-12T14:30:00Z", "word_count": 1842, "category": "Technology", "tags": "['AI', 'Machine Learning', 'Policy']"
| # | url | headline | subheadline | author | publish_date | updated_date |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Authors objects from vox.com. All fields typed and schema-versioned.
"name": "Kelsey Piper", "profile_url": "https://www.vox.com/authors/kelsey-piper", "twitter_handle": "@kelseytuoc", "article_count": 342, "role": "Senior Reporter", "last_published": "2026-05-12T14:30:00Z"
| # | author_id | name | profile_url | twitter_handle | bio | article_count |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Explainers objects from vox.com. All fields typed and schema-versioned.
"title": "Everything you need to know about AI policy", "card_count": 12, "topics": "['Technology', 'Politics']", "last_updated": "2026-04-18T09:15:00Z", "url": "https://www.vox.com/explainers/ai-policy", "visual_assets": 4
| # | explainer_id | title | summary | card_count | topics | last_updated |
|---|---|---|---|---|---|---|
| 1 | ||||||
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| 3 |
Complete list of extractable fields for Media & Embeds objects from vox.com. All fields typed and schema-versioned.
"media_type": "image", "source_url": "https://cdn.vox-cdn.com/thumbor/image.jpg", "caption": "A data centre in 2026.", "credit": "Getty Images", "width": 1200, "height": 800
| # | article_url | media_type | source_url | caption | credit | width |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Metadata objects from vox.com. All fields typed and schema-versioned.
"meta_title": "The future of generative models - Vox", "meta_description": "How new policies shape algorithm development.", "schema_type": "NewsArticle", "section": "Technology", "read_time": "8 min", "canonical_url": "https://www.vox.com/technology/2026/article-slug"
| # | url | meta_title | meta_description | og_image | canonical_url | schema_type |
|---|---|---|---|---|---|---|
| 1 | ||||||
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| 3 |
Our pipelines handle the complexities of modern media sites. We bypass infinite scroll, hydrate dynamic charts, and normalise inconsistent article templates into clean datasets.
Clean body text without navigation elements, advertisements, or related-article injected blocks.
Track journalists across sections. Extract bios, social handles, and publication histories.
Structured extraction of Vox Explainers, maintaining the relationship between individual cards and the parent topic.
Extract the hierarchy of topics and tags assigned to every piece of content.
Scrape historical content back to the 2014 launch, building a complete corpus.
Extract YouTube embeds, podcast links, and high-resolution image assets with captions.
Monitor RSS feeds and sitemaps to capture new articles within minutes of publication.
Map internal linking structures for SEO analysis and topic clustering.
Target specific sections or acquired properties with custom schema rules.
Brief in. Clean data out.
Provide categories, author URLs, or date ranges. We design the extraction schema together.
We configure Scrapy crawlers, handle pagination, and manage dynamic content rendering.
Schema validation, null-rate checks, and text-cleanliness verification before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket or BigQuery dataset on agreed cadence.
Media sites deploy complex frontend frameworks. Here is how we ensure reliable extraction from Vox Media properties.
Vox relies heavily on infinite scroll for category and author pages. We intercept the underlying API requests or use Playwright to trigger scroll events, ensuring total coverage of historical feeds.
Data journalism pieces often embed interactive visualisations. We execute JavaScript to capture the underlying data attributes or final rendered states of these elements.
Standard news articles, Explainers, and long-form features use different DOM structures. Our selectors recognise the template type and route extraction through the correct logic path.
News articles are frequently updated. We track the 'updated_date' metadata and emit diffs when an article changes, giving you a complete revision history.
We strip newsletter sign-up forms, inline advertisements, and 'Read More' injected links from the article body, delivering pure editorial text.
AI teams use the corpus of explanatory journalism to train models on clear, structured informational text.
PR firms and researchers track narrative shifts, topic frequency, and sentiment across major publications.
Publishers analyse internal linking structures, tag usage, and headline formats to optimise their own content.
Media analysts track author beats, publication velocity, and topic specialisation over time.
Rival media organisations benchmark output volume, category distribution, and engagement metrics.
Researchers extract Explainer cards to build structured databases of claims and context.
"Vox provides the highest density of explanatory journalism on the web, but extracting clean text from dynamic layouts requires purpose-built pipelines."
Media sites deploy complex frontend frameworks. Scraping Vox requires handling infinite scroll feeds, hydrating interactive charts, and normalising inconsistent article templates. DataFlirt manages this infrastructure so your data science team receives clean, structured text ready for NLP training.
Everything supported by our vox.com scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy handles crawl orchestration and deduplication. Playwright handles JavaScript rendering for interactive charts and infinite scroll feeds.
We maintain proxy pools to distribute requests, preventing rate-limiting and IP bans during high-volume archive extraction.
Pipelines run on AWS infrastructure. Airflow handles scheduling, ensuring daily updates are delivered on time. State is stored in PostgreSQL.
Data delivered to where your team already works — no new tooling required.
About vox.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available news articles is generally permissible. DataFlirt extracts only public, non-authenticated editorial content. We do not extract personal user data or bypass paywalls. Clients should review Vox Media terms of service and consult legal counsel for their specific use cases.
We use Playwright to execute JavaScript, trigger scroll events, and hydrate interactive elements. Where possible, we intercept the underlying API responses to extract data faster and cleaner than parsing the DOM.
Yes. We can traverse sitemaps and pagination to extract the complete historical corpus back to the site's launch, subject to content availability.
We monitor RSS feeds and sitemaps to capture new articles within minutes. Full category sweeps typically run daily or hourly depending on your requirements.
Our minimum engagement covers continuous tracking of specific categories or authors, or one-off historical dumps starting at 10,000 articles. Contact us for a scoped quote.
Yes. We provide a sample run of up to 500 articles to validate the schema, text cleanliness, and metadata extraction before contracting.
Explainers use a distinct template with individual cards. Our schema models this relationship, extracting each card as a distinct object linked to the parent Explainer topic.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a complete historical archive for LLM training or a daily feed of new articles. Tell us what you need.
