What is QualCoder?
QualCoder is an open-source, cross-platform qualitative data analysis application written in Python. It allows researchers to import textual data such as interview transcripts, social media posts, news articles, etc. and systematically code, annotate and analyze the data.
Key features of QualCoder include:
- Importing and managing textual documents and other file types like images, pdfs, audio and video.
- Applying hierarchical codes to segments of text using auto and manual coding.
- Writing analytic memos and linking them to codes and sources.
- Searching and filtering data on codes, memos and attributes.
- Statistical overviews of codes showing coverage and relations.
- Data visualization of codes and categories.
- Exporting coded data and reports.
As an open-source tool, QualCoder enables full customization of the software to suit specific research needs. It can be used by individual researchers and teams to manage small and large scale qualitative data analysis projects. The use of memos sets it apart from many QDA tools.
Overall, QualCoder allows systematic analysis of qualitative data while retaining links to sources and contexts from where the data is obtained. This leads to robust and transparent analysis.
NVivo, MAXQDA, ATLAS.ti, AQUAD, Julius, Transana, Dedoose, consider.ly, Taguette, RQDA, The Ethnograph, CATMA, Quirkos, Dovetail, Provalis Research, HyperResearch, f4analyse, Keeword bee, Annotations for Mac are some alternatives to QualCoder.