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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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**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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## π What's Inside?
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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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```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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## π Dataset Statistics
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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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## π― Why This Dataset Rocks
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### ποΈ **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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### π¬ **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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### π‘ **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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## π Data Structure
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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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## π οΈ Quick Start
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```python
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from datasets import load_dataset
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dataset = load_dataset("nick007x/phoronix-articles")
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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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## π Advanced Usage
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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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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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print(f"Found {len(hardware_articles)} hardware-focused articles")
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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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# 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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## β οΈ Important Notes
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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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## π License
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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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## π€ Citation
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If this dataset powers your research or project, please cite:
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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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## π Perfect For
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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
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