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经济教育学者学习什么? 机器学习的见解

Jose Manuel Fernandez,博士 E. Butter 持有人,K。
经济教育杂志。 四月5,2021

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本文的作者使用文本挖掘技术来揭示经济教育中的隐藏或潜在主题。 JEL代码的常见用法仅识别每篇论文的学术背景,而不能识别该论文涉及的基本经济概念。 一种称为Latent Dirichlet Allocation的无监督机器学习算法可用于识别经济教育学术工作中的15个隐藏主题。 文本挖掘模型通过查找不同文档中单词使用的相关性来识别经济教育主题。 作者表明,这些新近确定的研究主题比通常采用的JEL代码解释了更多的引文计数变化。 此外,特定期刊显示了经济教育研究中某些主题的偏好。

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