Analyzing knowledge flows of scientific literature through semantic links: a case study in the field of energy

Abstract

In this paper we propose a new technique to semantically analyze knowledge flows across countries by using publication and citation data. We start with the identification of research topics produced by a given source country. Then, we collect papers, published by the authors outside the source country, citing the identified research topics. At last, we group each set of citing papers separately to determine the scholarly impact of the actual identified research topics in the cited topics. The research topics are identified using our proposed topic model with distance matrix, an extension of classic Latent Dirichlet Allocation model. We also present a case study to illustrate the use of our proposed techniques in the subject area Energy during 2004–2009 using the Scopus database. We compare the Japanese and Chinese papers that cite the scientific literature produced by the researchers from the United States in order to show the difference in the use of same knowledge. The results indicate that Japanese researchers focus in the research areas such as efficient use of Photovoltaic, Energy Conversion and Superconductors (to produce low-cost renewable energy). In contrast with the Japanese researchers, Chinese researchers focus in the areas of Power Systems, Power Grids and Solar Cells production. Such analyses are useful for understanding the dynamics of the relevant knowledge flows across the nations.