In simple English
QualCoder helps researchers analyze interviews, documents, and media recordings by organizing text into searchable themes. You can import documents in many common formats, highlight sections of interest, and group them into categories. It runs entirely on your own computer so your sensitive interview data stays private. You can optionally connect an artificial intelligence model to help explore your research material. The software is completely free to use without any ongoing subscription fees.
What it is
QualCoder is a qualitative data analysis application written in Python and built with PyQt6 (a framework for creating graphical desktop applications with Python). It provides tools for coding text, images, audio, and video selections, managing hierarchical categories, and generating visual reports.
What it is good for
Social scientists, qualitative researchers, and students who need a free, open-source alternative to expensive proprietary software like NVivo or ATLAS.ti to code interview transcripts and analyze research data.
- Runs locally on your computer, keeping all qualitative data completely private.
- Supports a wide variety of input formats including PDF, Word documents, audio, and video files.
- Includes optional integration with external AI models for automated text exploration and summarization.
- Requires installing Python and managing a virtual environment if you install from source.
- Desktop app bundles from the release page may trigger security warnings on Windows and macOS because they lack a paid publisher certificate.
- Audio and video coding can be unstable or unsupported on certain Linux distributions like Fedora due to multimedia library conflicts.
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git clone https://github.com/ccbogel/QualCoder.git cd QualCoder python3 -m venv env source env/bin/activate pip install --upgrade pip pip install -r requirements.txt cd src python3 -m qualcoder