We extract headlines, article bodies, author metadata, and publication timelines from Aftenposten. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Article Metadata objects from aftenposten.no. All fields typed and schema-versioned.
"article_id": "8J9K2L", "headline": "Nytt byråd på plass i Oslo", "author_name": "Kari Nordmann", "published_date": "2026-03-14T08:30:00Z", "category": "Oslo", "is_paywalled": true, "url": "https://www.aftenposten.no/oslo/i/8J9K2L/nytt-byrad"
| # | url | article_id | headline | subheadline | author_name | published_date |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Full Text Content objects from aftenposten.no. All fields typed and schema-versioned.
"article_id": "8J9K2L", "body_text": "Det nye byrådet presenterte i dag sin plattform...", "word_count": 845, "reading_time_minutes": 4, "pull_quotes": "['Vi må prioritere kollektivtrafikken.']", "embedded_links": "['https://www.aftenposten.no/oslo/i/1A2B3C/tidligere-sak']"
| # | article_id | headline | body_text | pull_quotes | image_urls | embedded_links |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Author Profiles objects from aftenposten.no. All fields typed and schema-versioned.
"author_id": "auth_4829", "name": "Kari Nordmann", "role": "Politisk kommentator", "twitter_handle": "@karinordmann", "article_count": 342, "profile_url": "https://www.aftenposten.no/profil/kari-nordmann"
| # | author_id | name | profile_url | role | bio | twitter_handle |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Frontpage Tracking objects from aftenposten.no. All fields typed and schema-versioned.
"snapshot_time": "2026-03-14T09:00:00Z", "position_index": 1, "module_name": "toppsak", "headline": "Nytt byråd på plass i Oslo", "is_breaking": false, "url": "https://www.aftenposten.no/oslo/i/8J9K2L/nytt-byrad"
| # | snapshot_time | position_index | module_name | headline | url | is_breaking |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Comments Data objects from aftenposten.no. All fields typed and schema-versioned.
"article_id": "8J9K2L", "comment_count": 124, "comments_open": true, "top_comment_author": "Ola Hansen", "upvote_count": 45, "thread_depth": 3
| # | article_id | comment_count | comments_open | top_comment_text | top_comment_author | upvote_count |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our pipeline handles the Schibsted platform structure, navigating dynamic frontpages, paginated section archives, and complex article layouts with mixed media.
Capture headlines, subheadlines, publication timestamps, modification dates, and categorisation tags for every published piece.
Extract clean body text, pull quotes, and embedded links while stripping out advertisements and tracking scripts.
Map articles to author profiles, extracting bylines, contact information, social handles, and historical publication counts.
Monitor the main Aftenposten frontpage at high frequency to track how long specific articles hold top positions.
Identify whether content is open or requires a Schibsted subscription, allowing accurate mapping of premium vs free content.
Extract high-resolution image URLs, captions, and video embed links associated with news articles.
Track engagement metrics including total comment counts and thread activity on open discussion articles.
Traverse date-based archives and section pagination to extract years of historical news data.
Run continuous pipelines that detect newly published articles and modifications to existing content.
Brief in. Clean data out.
Provide section URLs, author lists, or date ranges. We design the extraction schema together.
We configure Scrapy crawlers, proxy rotation, and session management to handle Aftenposten infrastructure.
Schema validation, null-rate checks, and content parsing verification before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Aftenposten operates on modern media infrastructure. Here is how we maintain reliable extraction pipelines.
Aftenposten article layouts vary significantly between standard news, long-form features, and live blogs. Our parsers use multi-layered fallback selectors to normalise content extraction across all template types.
High-frequency scraping triggers rate limits and blocks. We distribute requests across Norwegian residential IP pools to maintain access without interruption.
We manage cookie states and local storage to prevent tracking loops and ensure consistent page rendering during extraction runs.
News articles are frequently updated after initial publication. We hash article content and track modification timestamps to deliver precise diffs of evolving stories.
Media sites update their frontend frameworks regularly. Our monitoring stack alerts on extraction failures or missing fields immediately, allowing rapid parser updates.
PR agencies and corporate communications teams track brand mentions, executive coverage, and crisis developments in real time.
Machine learning teams use clean, high-quality Norwegian text corpora to train language models and sentiment classifiers.
Researchers and think tanks track political coverage, topic frequency, and editorial bias across election cycles.
Other media organisations monitor Aftenposten publication velocity, frontpage strategies, and author output.
Quantitative funds extract market-moving news, corporate announcements, and macroeconomic reporting for algorithmic trading signals.
Universities compile historical datasets of public discourse, cultural trends, and linguistic evolution over decades.
"Aftenposten represents the definitive record of Norwegian current affairs. Extracting this corpus at scale requires navigating complex paywall logic and dynamic frontpage modules."
Media monitoring requires absolute reliability. Aftenposten uses sophisticated delivery networks and bot protection logic. DataFlirt manages the residential proxy rotation, session handling, and schema maintenance required to extract article data consistently, allowing your team to focus entirely on downstream analysis.
Everything supported by our aftenposten.no 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 high-throughput URL discovery, archive traversal, and content deduplication across the Aftenposten sitemap.
We route requests through Norwegian proxy endpoints to ensure content is served exactly as local readers experience it.
Airflow schedules extraction runs, manages retries, and pushes normalised data to your designated storage sink.
Data delivered to where your team already works — no new tooling required.
About aftenposten.no scraping, legality, and pipeline operations.
Ask us directly →By default, we only extract the publicly visible portions of paywalled articles alongside their metadata. If you possess a valid Schibsted enterprise subscription, we can configure the pipeline to authenticate using your credentials to extract full text.
For frontpage tracking and breaking news detection, pipelines can be configured to run at 5-minute intervals. Full archive sweeps typically run on a daily cadence.
Yes. We can traverse Aftenposten section archives and sitemaps to extract historical articles dating back to the limits of their digital platform.
Scraping publicly available factual data and headlines is generally permissible. However, full article text is subject to copyright law. Clients using full-text extraction for commercial purposes must ensure they have the appropriate licensing or fall under fair use exemptions for NLP training or research. DataFlirt provides the extraction infrastructure; clients are responsible for data usage compliance.
Our parsers use fallback selector chains. If Aftenposten introduces a new article template, our monitoring detects missing fields and alerts our engineering team to update the extraction schema, typically within 24 hours.
We can extract comment counts and top-level discussion data where Aftenposten enables public commentary. Deep thread extraction requires specific pipeline configuration.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a historical archive dump or a continuous feed of breaking news and metadata, we build and operate the infrastructure. Specify your requirements today.
