metadata

license: mit
task_categories:
  - text-classification
  - text-generation
  - sentence-similarity
  - text2text-generation
language:
  - en
tags:
  - code
size_categories:
  - 100K<n<1M

GitHub Repo Metadata 5★ — Developer History and Profiling Dataset

📘 Paper (FSE 2025) 💻 Codebase
📊 Source Dataset on Kaggle

Dataset Summary

This dataset provides a processed and enriched version of the "GitHub Repository Metadata with 5 Stars" dataset, reformatted to support developer modeling and task recommendation research.

We provide several views of the data that are tailored for:

Developer-level sequence modeling
Socio-technical profiling
Text-based representation learning
Hybrid retrieval and recommendation tasks

This dataset is used in our FSE 2025 paper:
SODAOpt: Socio-Demographic and Textual Adaptive Fusion for Optimizing Developer Task Assignment.

Dataset Structure

This dataset is available in .parquet format and includes:

File	Description
`textual_history.parquet`	Concatenated per-user textual views of repositories
`id_history.parquet`	Developer → repository interaction histories using hashed IDs
`user_descriptions.parquet`	Structured per-user summaries with stars, forks, top languages
`repo_info.parquet`	Clean table of repositories with hashed `repo_id` and `language_id`
`mappings/item_id_map.json`	Mapping of hashed `repo_id` to sequential numeric `item_id`
`mappings/language_mapping.parquet`	Mapping of language names to numeric `language_id`

Use Cases

🔍 Retrieval-based developer-task matching
🧠 Developer embedding learning
🧮 Evaluation of sequence models in software engineering
🧬 Pretraining/finetuning for software-oriented LLMs

How to Cite

@misc{zjkarina_2025_sodaopt,
    title = {SODAOpt: Social Dialogue Optimization Dataset},
    author = {Karina Romanova and Sergey Senichev and Lina Veltman and Ivan Nasonov and Andrey Kuznetsov and Ilya Makarov},
    month = {April},
    year = {2025},
    url = {https://huggingface.co/datasets/zjkarina/SODAOpt}
}

Original Dataset

Pelmers. (2023). GitHub Repository Metadata with 5+ Stars. Kaggle.
https://www.kaggle.com/datasets/pelmers/github-repository-metadata-with-5-stars

Derived Work

Romanova, K., Senichev, S., Veltman, L., Nasonov, I., Kuznetsov, A., & Makarov, I. (2025).
SODAOpt: Socio-Demographic and Textual Adaptive Fusion for Optimizing Developer Task Assignment.
In Proceedings of the 33rd ACM International Conference on the Foundations of Software Engineering (FSE ’25).