Mejia Cristian, Kajikawa Yuya
Graduate School of Environment and Society, Tokyo Institute of Technology, Tokyo, Japan.
Institute for Future Initiatives, The University of Tokyo, Tokyo, Japan.
Front Res Metr Anal. 2021 May 13;6:652285. doi: 10.3389/frma.2021.652285. eCollection 2021.
This paper applied a literature-based discovery methodology utilizing citation networks and text mining in order to extract and represent shared terminologies found in disjoint academic literature on food security and the Internet of Things. The topic of food security includes research on improvements in nutrition, sustainable agriculture, and a plurality of other social challenges, while the Internet of Things refers to a collection of technologies from which solutions can be drawn. Academic articles on both topics were classified into subclusters, and their text contents were compared against each other to find shared terms. These terms formed a network from which clusters of related keywords could be identified, potentially easing the exploration of common themes. Thirteen transversal themes, including blockchain, healthcare, and air quality, were found. This method can be applied by policymakers and other stakeholders to understand how a given technology could contribute to solving a pressing social issue.
本文应用了一种基于文献的发现方法,利用引文网络和文本挖掘技术,从关于食品安全和物联网的不相关学术文献中提取并呈现共享术语。食品安全主题包括营养改善、可持续农业以及许多其他社会挑战方面的研究,而物联网则指的是一系列可从中获取解决方案的技术。关于这两个主题的学术文章被分类为子集群,并相互比较其文本内容以找到共享术语。这些术语形成了一个网络,从中可以识别出相关关键词的集群,这可能有助于对共同主题的探索。发现了包括区块链、医疗保健和空气质量在内的13个横向主题。政策制定者和其他利益相关者可以应用这种方法来了解特定技术如何有助于解决紧迫的社会问题。