This is the replication package for "Documenting Ethical Considerations in Open Source AI Models", accepted by 18th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM'24).
qualitative codescontains our thematic analysis codes for documents from three data sources.mine_repositoriesfolder contains code for mining repositories on both GitHub and Hugging Face.duplicate_detectionsection contains the code we used to detect document reuse.Curated documentsfolder contains documents we mined on three data sources. You can cross reference these raw documents with our codes underqualitative codesfolder.
We will provide a more detailed folder explaination below.
categories_mindmap.pdf contains the mindmap describing the hierarchical relationship for how base codes are synthesised into concepts and then categories.
codes contains the code number and its description.
sample_hf_mc contains the document name, keypoints, codes for the data source of HF_CARD.
sample_gh_rm contains the document name, keypoints, codes for the data source of GH_README.
sample_gh_mc contains the document name, keypoints, codes for the data source of GH_CARD.
This folder contains the mining procedure as well as the keyword expansion procedure. The keyword-base.txt is used for initial keyword filtering. After keyword_filter_expansion.py, which is used to expand the keyword set based on the process we described in the paper, we get extra_keywords_paragraph.txt.
This folder contains the code for detecting duplicate documents. Please refer to section 3.3 in our paper for details. duplicate_detection.py for is responsible for generating similarity matrix and performing clustering.
This folder contains our collected documents. There are three subfolders in it, github_model_card_documents, github_readme_documents, and huggingface_model_card_documents corresponds to terms GH_CARD, GH_README, and HF_CARD respectively in our paper. Please note that this is the raw data before any filters.