DeTAILS: Deep Thematic Analysis with Iterative LLM Support. DeTAILS is a toolkit for Thematic Analysis (and qualitative coding). By grounding LLMs in your research, DeTAILS automates the heavy lifting—scanning transcripts for quotes, generating codes and themes—while you (the researcher) guide the analysis to ensure rigor and depth.
Classify, extract, and summarize open-ended text (survey responses, social media, academic papers, political text, web content) at scale with LLMs. Python, R, and Stata.
Computer-Assisted Qualitative Data Analysis Software (CAQDAS) for coding textual data, retrieving coded segments, and analysing patterns
A local-first CAQDAS for Obsidian: mixed-methods analysis with multi-modal qualitative coding, case variables, built-in analytics, and REFI-QDA interop (Atlas.ti / NVivo / MAXQDA).
A method-agnostic qualitative data analysis software
Better Notes templates that turn Zotero into a simple qualitative-coding tool: Code Report and Theme Document, with a user guide
Supplementary coding matrix for The Irreducible Human (Smarason & Guttesen): 19 civilisational traditions x 7 capacities, with tallies and excluded candidates.
A curated collection of research tools, academic writing templates, and markdown files. Designed to help students and researchers organize literature reviews, qualitative data, thesis structures, and research workflows efficiently.
eQc - Easy Qual Coding, a desktop software for QDA
HITL Streamlit platform for bilingual contingency scoring of CGM interview answers (synthetic demo data only)
An alternative, ease-of-use, implementation of HICode (autonomous Hierarchical Inductive Coding approach with LLMs) and a rich streamlit dashboard
TACIT: LLM-assisted qualitative coding that keeps the record: where the codebook came from, what the model proposed, and what the researcher changed. Python + Streamlit; Gemini, Ollama or any OpenAI-compatible server; transcripts can stay on your machine. pip install tacit-qda
Workshop and training materials for qualitative data analysis
Thematic coding of open-ended survey text without a predefined codebook. Claude Opus 4.5 infers each question from the answers rather than the header, clusters 3 to 5 themes, and classifies every participant with no orphans; GPT-5.1 writes the executive layer. Quotes are verified against their source row and deduplicated across themes.
Zero-code text analysis toolkit for social science researchers | 面向社会科学研究者的零代码文本分析工具包
Structured evaluation of 30 support bot conversations measuring containment, escalation rate, intent accuracy, and CSAT correlation, LLM-assisted qualitative coding, edge cases, and recommendations.
AI-assisted coding workspace for open-ended survey and interview responses
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