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Open Datasets
StackLite — Stack Overflow Question Dataset (2016)
Text

StackLite — Stack Overflow Question Dataset (2016)

This StackLite dataset contains metadata for questions asked on Stack Overflow up to October 2016. Data includes ID, dates, scores, tags, and number of responses. It allows you to analyze trends and correlations between tags and temporal behaviors.

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Size

Over 12 million CSV/SQLite questions, with associated metadata

Licence

Creative Commons Attribution-ShareAlike (CC BY-SA)

Description

The dataset StackLite offers an excerpt of Stack Overflow questions, focusing on metadata: identifiers, dates, scores, tags, number of answers, and user information. This simplified format facilitates statistical and temporal analysis of programming questions.

What is this dataset for?

  • Analyze the evolution of questions by tags over time
  • Study the correlations between tags and question scores
  • Explore publishing trends by days of the week

Can it be enriched or improved?

Yes, it is possible to add text, questions and answers, or additional user data for finer analyses. A qualitative annotation of questions could also increase its value.

🔎 In summary

Criterion Evaluation
🧩 Ease of use⭐⭐⭐⭐⭐ (Simple CSV/SQLite format, very accessible)
🧼 Need for cleaning⭐⭐⭐⭐⭐ (Low – well-structured and clean data)
🏷️ Annotation richness⭐⭐⭐✩✩ (Medium – detailed metadata but no textual content)
📜 Commercial license✅ Yes (CC BY-SA)
👨‍💻 Beginner friendly🌟 Yes, perfect for first data analysis projects
🔁 Fine-tuning ready⚠️ Limited – not suitable for NLP without textual content
🌍 Cultural diversity⚠️ Mostly English, global developer community

🧠 Recommended for

  • Data scientists
  • Tech trend analysts
  • Community Studies Researchers

🔧 Compatible tools

  • Pandas
  • SQL
  • Jupyter
  • Table
  • PowerBI

💡 Tip

Use in conjunction with the full Stack Exchange dumps for in-depth text analysis.

Frequently Asked Questions

Does this dataset contain the full text of questions and answers?

No, question metadata only. The full text can be found in other larger dumps.

Can this dataset be used to analyze trends in technology?

Yes, it is ideal for observing the popularity and evolution of tags related to programming technologies.

Is this dataset suitable for training an NLP model?

Not directly, as it does not contain textual content, but it can be used as a complement for statistical analyses.

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