使用ChatGPT自动化科学摘要的内容分析:一种方法学协议和用例
Adrián Domínguez-Diaz1, Manuel Goyanes2, Luis de-Marcos1
1Computer Science, Universidad de Alcalá, Madrid, Spain.
MethodsX
|July 4, 2025
概括
本研究介绍了在内容分析中使用ChatGPT的协议,表明AI可以提高编码效率. 清晰的定义对于人工智能的准确性至关重要,特别是在复杂的研究方法中.
科学领域:
- 人工智能的人工智能
- 计算社会科学 计算社会科学
- 研究方法研究方法研究方法学
背景情况:
- 内容分析是一个关键的研究方法.
- 手动内容分析可能耗时且资源密集.
- 人工智能 (AI) 的整合为自动化和增强研究过程提供了潜力.
研究的目的:
- 为在内容分析中使用ChatGPT提供一个验证的协议.
- 评估人工智能驱动的内容分析的有效性和局限性.
- 探索方法明确性对研究AI绩效的影响.
主要方法:
- 开发了一个结构化的协议,用于将代码书转换为用于ChatGPT的AI可读提示.
- 该协议通过分析980篇研究文章来验证,以确定研究方法和数据收集方法.
- 使用定量指标评估性能,将AI结果与既定编码标准进行比较.
主要成果:
- 聊天GPT在识别数据收集方法方面表现出高准确度.
- 根据研究方法的表现有所不同:定量 (0.96),定性 (0.82),混合方法 (0.60).
- 挑战被确定为定义不完善,代表性不足或层次复杂的类别.
结论:
- 开发的协议提高了编码效率,并显示了AI在内容分析方面的可行性.
- 清晰的方法定义对于优化人工智能性能至关重要,特别是在混合方法研究中.
- 像ChatGPT这样的AI工具显示出了简化研究编码的巨大潜力,并得到了interrater可靠性指标的支持.
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