The paper investigates how large language models (LLMs) can perform multi-coder qualitative coding by independently coding, debating, and reconciling disagreements. It quantifies the effectiveness of this approach across diverse datasets, identifying key factors—such as codebook length, data similarity, and agent disagreement—that influence coding accuracy. The study finds that intense, unresolved debates improve accuracy but that LLMs still lack adaptive responsiveness to context, leading to design recommendations for automated coding systems.
By Jeongyeon Kim, John Mitchell
QuAD is a framework that quantitatively assesses the quality of qualitative response datasets before analysis. It compares an intrinsic cluster distribution derived from the responses with an extrinsic, researcher-defined analytical lens based on metadata, using a four‑quadrant assessment that considers lens‑level relations and within‑cluster variation. The method employs a content‑aware multi‑agent system with two‑stage instruction generation and adaptive anchors to improve scoring consistency, and is validated through synthetic experiments and a real‑world social survey case study.
By Wenshuo Zhang, Leixian Shen, Qiqi Zhou, Shuchang Xu, Feiyang Hao, Huamin Qu, Haobo Li, Zhao Chen, Lin-Ping Yuan
arXiv:2601. 14171v2 Announce Type: replace Abstract: Writing effective rebuttals is a high-stakes task that demands more than linguistic fluency, as it requires precise alignment between reviewer intent and manuscript details.
By Qianli Ma, Chang Guo, Zhiheng Tian, Siyu Wang, Jipeng Xiao, Yuanhao Yue, Zhipeng Zhang
arXiv:2608.30543v1 Announce Type: new
Abstract: Large Language Models (LLMs) offer new possibilities for scaling qualitative analysis, but existing applications often provide limited methodological t...
By Nadia Jul Jeldtoft, Tariq Yousef
DataSTORM is an LLM‑based agentic system designed to conduct deep research over large‑scale structured databases and internet sources. It applies principles of Exploratory Data Analysis and Data Storytelling to frame research as a thesis‑driven analytical process, iteratively generating hypotheses, performing quantitative reasoning, and crafting coherent narratives. Evaluations on InsightBench and a new ACLED‑based dataset show that DataSTORM surpasses existing systems, achieving significant improvements in insight‑level recall and summary‑level scores.
By Shicheng Liu, Yucheng Jiang, Sajid Farook, Camila Nicollier Sanchez, David Fernando Castro Pena, Monica S. Lam
arXiv:2607. 28889v1 Announce Type: cross Abstract: Qualitative researchers increasingly encounter interaction corpora whose scale exceeds what manual coding alone can address, and large language models (LLMs) are frequently proposed as analytic assistants.
By Alex Liu, Min Sun, Lief Esbenshade, Michael Xiao, Victor Tian, Zachary Zhang, Kevin He