Measuring tech emergence: A contest
Measuring tech emergence: A contest
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DOI：
10.1016/j.techfore.2020.120176
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发表时间：
2020-10
影响因子：
12
通讯作者：
A. Porter;Denise Chiavetta;Nils C. Newman
中科院分区：
文献类型：
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作者：
A. Porter;Denise Chiavetta;Nils C. Newman
我们举办了一个竞赛来预测高度活跃的研究课题。参与者分析了一个目标技术领域（合成生物学）十年来的Web of Science摘要记录，以指出未来两年可能积极追求的前沿子主题。我们描述了由13个参赛队提供的比赛程序和结果。参赛者使用各种专题和其他领域的抽象记录；有些是用外部数据增强的。他们应用了至少19种不同的方法来得出预计在未来两年内将积极研究的新兴主题。除了专题文本分析外，参赛者还采用了不同的方法，包括向后和向前引文分析以及网络分析，以帮助确定在不久的将来可能被高度研究的主题。这种利用广泛的文本分析和其他文献计量工具预测近期研究活动的公共练习提供了令人兴奋的资源。
We conducted a contest to predict highly active research topics. Participants analyzed ten years of Web of Science abstract records in a target technological domain (synthetic biology) so as to indicate cutting edge sub-topics likely to be actively pursued in the following two years. We describe contest procedures and results provided by thirteen participating teams.Contestants used various topical and other fields in the abstract records; some augmented with external data. They applied at least 19 diverse methods in deriving emerging topics predicted to be actively researched in the coming two years. Besides topical text analyses, contestants variously brought to bear both backward and forward citation analyses, and network analyses, to help identify topics apt to be highly researched in the near future. This communal exercise on forecasting near-future research activity using a wide array of text analytic and other bibliometric tools provides a stimulating resource.