Understanding Public-Access Cyberlearning Projects Using Text Mining and Topic Analysis

David McArthur; Helen Crompton

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Understanding Public-Access Cyberlearning Projects Using Text Mining and Topic Analysis

机译：使用文本挖掘和主题分析了解公共访问网络学习项目

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The federal government has encouraged open access to publicly funded federal science research results, but it is unclear what knowledge can be gleaned from them and how the knowledge can be used to improve scientific research and shape federal research policies. In this article, we present the results of a preliminary study of cyberlearning projects funded by the National Science Foundation (NSF) that address these issues. Our work demonstrates that text-mining tools can be used to partially automate the process of finding NSF's cyberlearning awards and characterizing the fine-grained topics implicit in award abstracts. The methodology we have established to assess NSF's cyberlearning investments should generalize to other areas of research and other repositories of public-access documents.

机译：联邦政府鼓励开放获取由公共资助的联邦科学研究成果，但是目前尚不清楚可以从中获取什么知识，以及如何将这些知识用于改善科学研究和制定联邦研究政策。在本文中，我们介绍了由美国国家科学基金会（NSF）资助的针对这些问题的网络学习项目的初步研究结果。我们的工作表明，文本挖掘工具可用于部分自动化寻找NSF的网络学习奖励并表征奖励摘要中隐含的细粒度主题的过程。我们建立的评估NSF网络学习投资的方法应该推广到其他研究领域和其他公共获取文档存储库。

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《Journal of the American Society for Information Science and Technology》 |2012年第11期|2146-2152|共7页
作者
David McArthur; Helen Crompton;
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University of North Carolina at Chapel Hill, CB 3500, Chapel Hill, NC, 27510;

University of North Carolina at Chapel Hill, CB 3500, Chapel Hill, NC, 27510;

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Understanding Public-Access Cyberlearning Projects Using Text Mining and Topic Analysis

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