Ever since I started engaging with Qualitative Data Analysis (QDA), the one thing that has consistently bothered me is the limited range of QDA software. The ecosystem either requires a user to subscribe and access robust, battle-tested tools or to rely on free and open-source projects that, most of the time, helped but sometimes did not meet requirements.
Although my data is always in plain text, the issue began biting hard when various options I tried started crashing midway through the analysis. I stubbornly avoided relying on subscription tools and tried something with a one-time fee, but that failed too, crashing after I had coded roughly 50 of my few hundred items. The developers did issue me a full refund and acknowledged the limitation. Thanks to them for the gesture, but the work had to be redone.
But then, why should QDA software struggle with handling a few hundred plain-text items? After all, they rely on SQL under the hood, and SQL is synonymous with reliability and scalability. That’s when I decided to try making something that could handle my dataset, or in extreme cases, a hundred times more. Large Language Models have considerably democratised programming, with the caveat that full responsibility lies with the developer to learn some fundamentals, iterate, and verify thoroughly to avoid producing seemingly correct or working outputs that are actually disastrous. Though challenging, I worked on the idea over the past few months, and finally, the efforts culminated in what I call Lattice. After over 600 iterations, it did not flinch with my dataset or even with a synthetic dataset of several thousand documents during the stress test.
Lattice is fully free and open-source under the
GNU Affero General Public License v3. It works on Windows and can import text as data from various file formats. It can handle texts in various languages and produce well-structured reports and visualisations.
If QDA of text interests you, please give it a try. I would love to hear feedback.
Webpage: https://lattice.jaisal.inGitHub: https://github.com/ekjaisal/LatticeZenodo: https://doi.org/10.5281/zenodo.20271310Announcement: https://www.linkedin.com/feed/update/urn:li:activity:7462504436691574784
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