Moreover, using complex QDA software may create a feeling for the researcher that they are forced to work within the software structuresĥ.

In fact, research has shown that learners of complex qualitative tools often struggle with confusions, frustrations, and feelings of inadequacyĤ. However, learning to use these complex software tools may be inconvenient for some researchers.

For example, a study found that 763 published articles in the Scopus database (between 19) used Atlas.ti and NVivo in their work, and that the majority of these studies were published in health sciences journalsģ. We hope this open-source software will facilitate qualitative data analysis by researchers who are interested in using Word for this purpose.Ĭommercial qualitative data analysis (QDA) software tools such as NVivo, MAXQDA and Atlas.ti seem to be the most popular in the qualitative research communityĢ, especially in health research. We also demonstrate that the software has satisfactory performance on a large dataset of Iranian journals abstracts. We illustrate how to use this software by conducting a preliminary content analysis on Tweets with the #successfulaging hashtag. It also offers basic visualization tools. WordCommentsAnalyzer provides an effective user interface to count codes, to organize codes in a code hierarchy, and to see various data extracts belonging to each code. NET Framework and OpenXml, which helps a qualitative researcher to organize codes when using Microsoft Word as the primary text markup software.

WordCommentsAnalyzer, a software tool that is written in C# using. However, organizing the keywords and categories in the comments can become a more difficult task when the amount of data increases. Word processing software like Microsoft Word provides a good editing experience, allowing the researcher to effortlessly add comments to text portions. There is a lack of free software that provides a professional and smooth experience in text editing and markup for qualitative data analysis.

Summaries in maxqda