Exploration of Shared Themes Between Food Security and Internet of Things Research Through Literature-Based Discovery.

Cristian Mejia,Yuya Kajikawa

doi:10.3389/frma.2021.652285

Abstract

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.

Highlights

Literature-based discovery (LBD) refers to text mining methodologies aimed at connecting disjoint literature by finding intermediary terms or concepts
The academic landscape of food security and Internet of Things (IoT) was examined by looking at clusters derived from citation networks of academic articles on each topic
A total of 77,559 articles was found in the largest component of the food security network, which can be grouped into 17 major clusters

Summary

Introduction

Literature-based discovery (LBD) refers to text mining methodologies aimed at connecting disjoint literature by finding intermediary terms or concepts. Swanson (Swanson, 1986) established a connection between Raynaud’s syndrome and fish oil as a potential treatment by mining academic articles on both topics and finding linking terms, such as blood viscosity. This treatment was validated through clinical trials. Researchers start with a seed term or topic, with subsequent steps to find related terms. This process can result in an ever-expanding list of related terms from where unexpected but valuable connections can be found.

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Conclusion