Skip to main content
All Reviews
PsychologyNiche
intermediate

CollabCoder: A Lower-barrier, Rigorous Workflow for Inductive Collaborative Qualitative Analysis with Large Language Models

Gao, Jie et al. (2024)

Published
May 11, 2024
Journal
Proceedings of the CHI Conference on Human Factors in Computing Systems
DOI
10.1145/3613904.3642002

At a GlanceAI

CollabCoder proposes an LLM-supported workflow to make rigorous inductive collaborative qualitative analysis more accessible.

SummaryAI

CollabCoder addresses the challenge of conducting collaborative qualitative analysis rigorously while reducing barriers for researchers. It introduces a workflow that incorporates large language models into inductive coding and analysis rather than treating them only as automated labelers. The work is relevant to researchers seeking practical ways to use LLMs in qualitative research while retaining a structured collaborative process.

Method SnapshotAI

The authors present CollabCoder, an LLM-supported workflow for inductive collaborative qualitative analysis.

BackgroundAI

Basic familiarity with qualitative coding, inductive analysis, and large language models is helpful.