AI助研新范式，自动完成从编码到发现的全流程
The AI Co-Ethnographer: How Far Can Automation Take Qualitative Research?
- 构建端到端流程，整合开放编码与模式发现
- 实现从原始文本到分析结论的自动化处理
- 适合需要高效深度分析的研究者使用
定性研究常涉及耗时费力的流程，难以在保持分析深度的同时规模化。本文提出一种名为AI协同人类学研究者（AICoE）的新颖端到端流程，旨在突破仅自动化编码分配的局限，提供更深度融合的方法。AICoE贯穿整个研究过程，涵盖开放编码、编码合并、编码应用以及模式发现，实现对定性数据的全面分析。
原文摘要 · Abstract (English)
Qualitative research often involves labor-intensive processes that are difficult to scale while preserving analytical depth. This paper introduces The AI Co-Ethnographer (AICoE), a novel end-to-end pipeline developed for qualitative research and designed to move beyond the limitations of simply automating code assignments, offering a more integrated approach. AICoE organizes the entire process, encompassing open coding, code consolidation, code application, and even pattern discovery, leading to a comprehensive analysis of qualitative data.
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