Qualitative data analysis app for text, images, audio, video
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QualCoder is a cross-platform qualitative data analysis application designed for researchers and academics working with text, image, audio, and video data. It provides tools for manual coding, hierarchical categorization, and report generation, with integrated AI capabilities for enhanced data exploration.
How It Works
QualCoder utilizes a Python backend with a PyQt6 GUI, enabling it to handle diverse data types. It supports manual coding of text segments, image regions, and audio/video selections. Codes can be organized hierarchically into categories. The application generates various reports, including visual coding graphs and frequency analyses. Notably, it integrates with AI models like OpenAI's GPT-4 and the Helmholtz Society's Blablador for advanced data analysis.
Quick Start & Requirements
.exe
for Windows, .dmg
for macOS) are available on the Releases page. Alternatively, installation from source is supported for Windows, macOS, and Linux (Ubuntu, Fedora, Arch/Manjaro).Highlighted Details
Maintenance & Community
QualCoder is an ongoing hobby project primarily developed by Dr. Colin Curtain, with contributions from Dr. Kai Dröge for AI features. Further community engagement details are not explicitly provided in the README.
Licensing & Compatibility
QualCoder is distributed under the LGPLv3 license. This license permits commercial use and linking with closed-source applications, but requires any modifications to QualCoder itself to be shared under the same license.
Limitations & Caveats
Pre-compiled application bundles may trigger security warnings from operating systems due to being from an "unknown publisher." The README notes that Wayland on Fedora might have compatibility issues with the Qt GUI, suggesting Xwayland installation. Some AI features may require paid API access.
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