Global Nanotechnology Research Literature
全球纳米技术研究文献计量分析

Text mining was used to extract technical intelligence from the global open nanotechnology and nanoscience research literature. An extensive nanotechnology/nanosciene-focuse query (300 term) was applied to the SCI/SSCI database. A novel addition was the use of phrase auto correlation maps to show technical thrust areas based on phrase co-occurrence in Abstracts, and the use of phrase-phrase cross-correlation maps to show technical thrust areas based on phrase relations due to the sharing of common co-occurring phrases. The use of factor matrices quantified further the strength of the linkages among institutions and among countries, and validated the co-publishing networks shown graphically on the maps.