聊天GPT自动定性研究:内容分析分析.
Rimke Bijker1, Stephanie S Merkouris2, Nicki A Dowling2
1Department of Psychology and Neuroscience, Auckland University of Technology, Auckland, New Zealand.
Journal of medical Internet research
|July 25, 2024
概括
在帮助定性内容分析方面,ChatGPT显得有前途,特别是在开发归纳编码方案方面. 它可以成为研究人员可靠的工具,但需要进一步的代来确认其在所有分析阶段的实用性.
科学领域:
- 计算社会科学 计算社会科学
- 研究中的人工智能.
- 定性数据分析 数据分析.
背景情况:
- 定性内容分析是耗时的,涉及数据检测,评估和编码.
- 像ChatGPT这样的大型语言模型为定性数据分析的自动化方面提供了潜力.
研究的目的:
- 评估ChatGPT在进行定性内容分析方面的有效性.
- 用ChatGPT分析论坛帖子关于减少糖的经验.
主要方法:
- 对537个论坛帖子进行了归纳和演内容分析.
- 提示工程用于指导ChatGPT进行数据分析任务.
- 将ChatGPT提取的数据与人类编码进行比较,以评估精度.
主要成果:
- 检测变化机制的精度在66%至88%之间.
- 编码器间协议得分 (κ) 不同,诱导方案显示更高的协议 (0.720.82).
- 聊天GPT在遵循指令方面表现出可靠性,特别是在诱导编码方案开发方面.
结论:
- 聊天GPT是一个相当可靠的助手,用于定性内容分析.
- 它擅长从数据中开发归纳编码方案,而不是演方法.
- 聊天GPT显示出作为第二编码器的潜力,需要进一步调查分析阶段的可靠性.
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