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- ---
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- license: mit
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ task_categories:
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+ - text-generation
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+ - text-classification
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+ - summarization
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+ - question-answering
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+ - topic-modeling
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+ - historical-analysis
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+ tags:
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+ - technology
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+ - open-source
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+ - linux
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+ - hardware
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+ - software
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+ - journalism
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+ - benchmarks
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+ - performance
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+ - phoronix
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+ - temporal-data
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+ - news-articles
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+ license: mit
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+ ---
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+ # Phoronix Articles Dataset: The Archive of Open-Source Computing Journalism
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+
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+ **The definitive dataset of Phoronix - your gateway to years of open-source hardware/software evolution, performance analysis, and Linux ecosystem journalism.**
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+
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+ ## πŸš€ What's Inside?
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+
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+ This dataset contains the complete archive of Phoronix articles - from bleeding-edge hardware launches to deep-dive Linux kernel analysis. Perfect for researchers, developers, and AI enthusiasts who need high-quality technical content.
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+
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+ ```python
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+ # Example entry showcasing the rich structure
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+ {
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+ "url": "https://www.phoronix.com/news/AMD-More-Cyan-Skillfish-2025",
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+ "title": "AMD Prepares Linux Driver Support For New APUs Still Relying On RDNA1 Graphics",
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+ "author": "Michael Larabel",
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+ "content": "It looks like AMD is preparing to introduce some new APUs/SoCs still relying on RDNA1-based graphics...",
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+ "comments_count": 25,
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+ "scraped_at": 1760718775.1247177
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+ }
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+ ```
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+
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+ ## πŸ“ˆ Dataset Statistics
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+
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+ - **Total Articles**: 50,000+ articles (estimated)
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+ - **Time Span**: 2004 to 2024 (20+ years of coverage)
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+ - **Authors**: Primarily Michael Larabel + contributors
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+ - **Content**: Full article text with metadata
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+ - **Format**: JSON Lines (.jsonl) - optimized for streaming
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+
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+ ## 🎯 Why This Dataset Rocks
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+
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+ ### πŸ—οΈ **Build Better AI Models**
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+ - **Technical NLP**: Train models on real-world hardware/software discourse
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+ - **Temporal Analysis**: Track technology adoption curves across 20+ years
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+ - **Domain-Specific LLMs**: Perfect foundation for open-source focused language models
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+
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+ ### πŸ”¬ **Research Powerhouse**
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+ - **Tech Trend Analysis**: From AMD vs Intel battles to the rise of ARM servers
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+ - **Open-Source Ecosystem Mapping**: Follow Linux, GNOME, Debian, Arch evolution
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+ - **Hardware Journalism Studies**: Analyze technical writing patterns over time
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+
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+ ### πŸ’‘ **Solve Real Problems**
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+ - **Benchmark Intelligence**: Extract performance insights across CPU/GPU generations
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+ - **Release Tracking**: Monitor Linux distro, kernel, and driver developments
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+ - **Community Engagement**: Study comment patterns on technical articles
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+
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+ ## πŸ” Data Structure
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+
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+ ```python
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+ {
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+ "url": "string", # Full article URL
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+ "title": "string", # Article title
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+ "author": "string", # Author name (mostly Michael Larabel)
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+ "content": "string", # Full article text with original formatting
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+ "comments_count": int, # Number of comments (engagement metric)
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+ "scraped_at": float # UNIX timestamp of collection
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+ }
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+ ```
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+
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+ ## πŸ› οΈ Quick Start
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+
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+ ```python
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+ from datasets import load_dataset
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+
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+ dataset = load_dataset("nick007x/phoronix-articles")
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+
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+ # Explore the treasure trove
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+ print(f"Loaded {len(dataset['train'])} articles spanning decades of tech journalism!")
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+ print(dataset['train'][0]) # Peek at the first article
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+ ```
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+
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+ ## πŸš€ Advanced Usage
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+
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+ ```python
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+ # Analyze hardware coverage trends
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+ dataset = load_dataset("nick007x/phoronix-articles", split="train")
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+
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+ hardware_articles = [article for article in dataset
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+ if any(term in article['title'].lower()
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+ for term in ['amd', 'intel', 'nvidia', 'arm', 'radeon'])]
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+
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+ print(f"Found {len(hardware_articles)} hardware-focused articles")
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+
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+ # Track author contributions
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+ from collections import Counter
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+ authors = Counter(article['author'] for article in dataset)
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+ print(f"Top authors: {authors.most_common(5)}")
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+
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+ # Temporal analysis
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+ import datetime
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+ dates = [datetime.datetime.fromtimestamp(article['scraped_at']).year
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+ for article in dataset]
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+ print(f"Coverage from {min(dates)} to {max(dates)}")
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+ ```
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+
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+ ## ⚠️ Important Notes
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+
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+ - **Copyright**: Article content belongs to Phoronix Media
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+ - **Intended Use**: Research, analysis, and AI training
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+ - **Commercial Use**: Check Phoronix's terms of service
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+ - **Attribution**: Please credit Phoronix when using their content
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+ - **Data Quality**: Clean UTF-8 text with original formatting preserved
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+
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+ ## πŸ“œ License
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+
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+ This dataset is released under the **MIT License** - use it for research, commercial projects, or whatever brilliant idea you have next!
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+
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+ ## 🀝 Citation
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+
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+ If this dataset powers your research or project, please cite:
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+
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+ ```bibtex
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+ @dataset{phoronix_articles_2025,
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+ title = {Phoronix Articles Dataset},
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+ author = {nick007x},
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+ year = {2025},
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+ publisher = {Hugging Face},
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+ url = {https://huggingface.co/datasets/nick007x/phoronix-articles}
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+ }
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+ ```
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+
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+ ## 🌟 Perfect For
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+
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+ - **AI Researchers** building domain-specific language models
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+ - **Data Scientists** analyzing technology adoption trends
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+ - **Open-Source Developers** understanding ecosystem evolution
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+ - **Tech Historians** studying computing journalism
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+ - **Students** learning about hardware/software landscape