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Uncovering Research Streams in the Data Economy Using Text Mining Algorithms

机译:使用文本挖掘算法发现数据经济中的研究流

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Data-driven business models arise in different social and industrial sectors, while new sensors and devices are breaking down the barriers for disruptive ideas and digitally transforming established solutions. This paper aims at providing insights about emerging topics in the data economy that are related to companies’ innovation potential. The paper uses text mining supported by systematic literature review to automatize the extraction and analysis of beneficial insights for both scientists and practitioners that would not be possible by a manual literature review. By doing so, we were able to analyze 860 scientific publications resulting in an overview of the research field of data economy and innovation. Nine clusters and their key topics are identified, analyzed as well as visualized, as we uncover research streams in the paper.
机译:数据驱动的商业模式出现在不同的社会和工业领域,而新型传感器和设备正在打破颠覆性观念的障碍,并以数字方式转变已建立的解决方案。本文旨在提供有关数据经济中与公司创新潜力相关的新兴主题的见解。本文使用了系统的文献综述支持的文本挖掘,以自动化提取和分析对科学家和从业人员均有益的见解,而人工文献综述则无法实现。通过这样做,我们能够分析860种科学出版物,从而概述了数据经济与创新研究领域。当我们在本文中发现研究流时,将识别,分析和可视化九个类群及其关键主题。

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