Buzz Feed Scraper

The Buzz Feed Scraper extracts articles and metadata from BuzzFeed.com, turning news content into structured data you can download or integrate into workflows. Whether you're tracking trending stories, analyzing publication patterns, or archiving articles, this tool helps you collect BuzzFeed content at scale — without manual browsing.

     

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Introduction

This scraper navigates BuzzFeed pages and identifies what counts as an article, then extracts rich data from each, including titles, authors, categories, publication dates, and full content. It’s aimed at media analysts, researchers, content teams, and anyone needing a clean feed of BuzzFeed articles.

Why Use It

• Collects large volumes of BuzzFeed articles automatically
• Outputs data in structured formats (JSON, CSV, Excel, HTML) for easy processing
• Helps monitor trending topics, authors, or categories over time
• Useful for sentiment analysis, content audits, or fake-news detection efforts

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Features

Feature	Description
Article Identification	Detects pages that are actual BuzzFeed articles.
Metadata Extraction	Scrapes article title, author, category, publication date, and other metadata.
Full Content Capture	Retrieves full article content (text, images, etc.).
Filtering	Allows filtering results by authors, topics, categories, or date ranges.
Bulk Crawling	Crawl many pages across the site with one run.
Multiple Output Formats	Export results as JSON, CSV, Excel, HTML or XML.
API / CLI Support	Use via Apify API, CLI, or SDK integrations. :contentReference[oaicite:0]{index=0}

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What Data This Scraper Extracts

Field Name	Field Description
url	URL of the article.
title	Article title.
author	Name of the author(s), if available.
category	BuzzFeed category or topic under which the article is published.
publishDate	Date when the article was published.
content	Full article text (and optionally markup).
images	Array of image URLs used in the article (if any).
tags	Tags, labels or topics associated with the article (if available).

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Example Output

[
  {
    "url": "https://www.buzzfeed.com/some-article",
    "title": "10 Things You Didn’t Know About …",
    "author": "John Doe",
    "category": "Lifestyle",
    "publishDate": "2025-12-05T14:30:00Z",
    "content": "<p>Here is the full article content...</p>",
    "images": [
      "https://img.buzzfeed.com/…/image1.jpg",
      "https://img.buzzfeed.com/…/image2.jpg"
    ],
    "tags": ["fun", "listicle"]
  }
]

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Directory Structure Tree

buzz-feed-scraper/
├── src/
│   ├── main.js
│   ├── crawler/
│   │   ├── page_fetcher.js
│   │   ├── article_parser.js
│   │   └── paginator.js
│   ├── utils/
│   │   ├── logger.js
│   │   └── url_normalizer.js
│   └── config/
│       └── settings.example.json
├── data/
│   ├── sample_input.json
│   └── sample_output.json
├── package.json
└── README.md

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Use Cases

• Media analysts aggregate BuzzFeed content to study trending topics or content performance.
• Researchers build datasets of articles for sentiment analysis, fact-checking, or academic work.
• Content teams curate lists of relevant BuzzFeed articles for newsletters, briefings, or social sharing.
• Journalism educators archive articles for teaching, referencing, or longitudinal analysis.
• Data-driven organizations monitor media output for brand mentions or public sentiment tracking.

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FAQs

Can I filter by publication date or author?
Yes — the scraper lets you specify filters like authors, categories, topics, or date ranges before running. :contentReference[oaicite:1]{index=1}

What output formats are supported?
JSON, CSV, Excel, HTML, and XML are supported — you can pick the one that suits your workflow. :contentReference[oaicite:2]{index=2}

Does it capture full article content and images?
Yes — full text plus associated images are captured when available. :contentReference[oaicite:3]{index=3}

Is using the scraper legal?
Scraping publicly available content is generally allowed, but reusing or publishing copyrighted material may be restricted depending on your use case and local regulations. Use responsibly. :contentReference[oaicite:4]{index=4}

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Performance Benchmarks and Results

Primary Metric:
Scrapes multiple articles in a single run — typical throughput: dozens of articles per minute depending on network and site load.

Reliability Metric:

99% successful runs reported by its maintainers over past usage history. :contentReference[oaicite:5]{index=5}

Efficiency Metric:
Outputs clean, normalized datasets with minimal overhead; suitable for daily or frequent scheduling.

Quality Metric:
Extracts comprehensive metadata and full content, enabling high-quality downstream analysis or integration.

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