![]() This is what MAXQDA looks like, with tags (codes) displayed in a document: If you are certain of exact matches in documents, it could be helpful as a feature. I ended up with some 330 codes/tags (to identify themes, patterns, and actors) and have assigned them in total almost 9000 times across the dataset.Ĭoding/tagging is manual work there is autocoding in MAXQDA which may help a bit though if you know you are looking for exact keyword matches (see my post above) but as I was looking for themes across a large dataset, not necessarily using the same keywords every single time (this was media coverage after all so people use different words to express the same ideas or thoughts), I did not use it much. I could predict some codes and themes in advance, but the majority of them have surfaced while actually coding/tagging). I have developed an extensive coding system (both inductive and deductive coding were used, i.e. The challenge was that I was faced with many documents to read and go through.Īs mentioned already in this thread, QDA software is great in that you tag (code) themes, patterns, etc. The idea was to find the most salient themes with regard to social, economic and political aspects and other issues surrounding the project and to identify the most prominent actors who were actively promoting or discussing them (it was a case study in communications and public relations). You are probably better off with DEVONthink but perhaps this may someday be helpful to someone else as well so here’s my take on it.Ī bit of a background as I feel understanding the use case is important: I did a content analysis (CA) on about 1300 pieces of media coverage of a particular project, spanning almost 20 years. I’ve been meaning to post this sooner but had been quite busy these days. A FREE lite-versionfor basic features and the suite of additional software may make it worth a look, though, if your computer is compatible.I am not sure whether this is entirely relevant to your question, but I used MAXQDA and DEVONthink while working on my master’s dissertation last year, so I have some experience with both however, I have used them for different purposes. QDA Miner - An older interface and no Mac support hinder this otherwise-solid and full-featured software.Dedoose - Designed for mixed methods projects with fewer but more complex codes (allows ratings), this full-featured online software is a solid choice in some circumstances, especially distributed groups with somewhat complex projects, or those that would benefit from monthly pricing.Atlas.ti Cloud - Slick and colorful, but not full-featured, this is a great software for first-time users with uncomplicated needs.Online: These make it easier to collaborate with others and offer per-month pricing, (~$10-15/month), good for shorter projects ![]() See this video on Qualitative Analysis Using Excel (TrixieMay Racer) Excel or Google Sheets or Calc - Any spreadsheet program can do basic code and retrieve using the filter and pivot table functions which all of them have.Best for those already using R for quantitative needs and desiring some mixed methods options. QCoder - R package with some point-and-click options (must install R first).Accepts Word documents, pdfs, images, and video, Takes a bit of work to get started, but easy to use once learned. More full-featured than other free options, including colors, cases, and right click menus ( see a video demonstration). Qualcoder - Python-based with an installer for Windows only (must run from source on Mac).Supports sensitive data with a local or server install, or use their free server. Taguette - Simple, but pleasant web interface supporting just basic code-and-retrieve.Those, combined with the increasingly restrictive and expensive licensing, has many looking elsewhere. But, annotations and memos are less integrated than they should be, and the Mac version has both fewer features and a different file type (hindering collaboration). NVivo- A streamlined and familiar interface and support for a variety of data types and organizational structures make NVivo a good all-around choice for any project.The interface tends to be more cluttered and redundant, but an identical interface across platforms, regular improvements, and free course licenses and read-only access to projects make it an attractive option. ![]()
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