Network Analysis and Natural Language Processing to Obtain a Landscape of the Scientific Literature on Materials Applications

Recent progress in natural languageprocessing (NLP) enables miningthe literature in various tasks akin to knowledge discovery. Obtainingan updated birds-eye view of key research topics and their evolutionin a vast, dynamic field such as materials science is challengingeven for experienced researchers. In this Perspective paper, we presenta landscape of the area of applied materials in selected representativejournals based on a combination of methods from network science andsimple NLP strategies. We found a predominance of energy-related materials,e.g., for batteries and catalysis, organic electronics, which includeflexible sensors and flexible electronics, and nanomedicine with varioustopics of materials used in diagnosis and therapy. As for the impactcalculated through standard metrics of impact factor, energy-relatedmaterials and organic electronics are again top of the list acrossdifferent journals, while work in nanomedicine has been found to havea lower impact in the journals analyzed. The adequacy of the approachto identify key research topics in materials applications was verifiedindirectly by comparing the topics identified in journals with diversescopes, including journals that are not specific to materials. Theapproach can be employed to obtain a fast overview of a given fieldfrom the papers published in related scientific journals, which canbe adapted or extended to any research area.