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This chapter presents the method developed by Garcia Quevedo et al. in Organizational Research Methods (2025) for qualitative analysis of large, unstructured datasets using large language models (LLMs). It addresses the limitations of traditional random sampling by proposing a structured approach that efficiently explores and selects relevant data for manual analysis. The method integrates three natural language processing (NLP) tasks: sentiment analysis, topic modeling, and information retrieval, allowing for comprehensive dataset exploration and selection. These tasks are covered in the subsequent chapters.

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Using LLMs in Qualitative Analysis

  • 章节

  • 出版模式：

    开放获取

  • 发表日期：

    2026年

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  • Diana Garcia Quevedo,
  • Josue Kuri

摘要

This chapter presents the method developed by Garcia Quevedo et al. in Organizational Research Methods (2025) for qualitative analysis of large, unstructured datasets using large language models (LLMs). It addresses the limitations of traditional random sampling by proposing a structured approach that efficiently explores and selects relevant data for manual analysis. The method integrates three natural language processing (NLP) tasks: sentiment analysis, topic modeling, and information retrieval, allowing for comprehensive dataset exploration and selection. These tasks are covered in the subsequent chapters.