No abstract

Text mining was used to extract technical intelligence from the open source global nanotechnology and nanoscience research literature. An extensive nanotechnology/nanosciencefocused query was applied to the Science Citation Index/Social Science Citation Index (SCI/SSCI) databases. The nanotechnology/nanoscience research literature infrastructure (prolific authors, key journals/institutions/countries, most cited authors/journals/documents) was obtained using bibliometrics. A novel addition was the use of institution and country auto-correlation maps to show co-publishing networks among institutions and among countries, and the use of institutionphrase and country-phrase cross-correlation maps to show institution networks and country networks based on use of common terminology (proxy for common interests). 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. BackgroundDue to the exponential growth of the open nanotechnology literature, there is need for gaining an integrated quantitative perspective on the state of this literature.

No abstract

Nanotechnology, Nanoscience, Text mining, Electronics, Applications, Health, O31, O32, O33,

This paper uses complementary text mining techniques to identify and retrieve the high impact (seminal) nanotechnology literature over a span of time. Following a brief scientometric analysis of the seminal articles retrieved, these seminal articles are then used as a basis for a comprehensive literature survey of nanoscience and nanotechnology. The paper ends with a global analysis of the relation of seminal nanotechnology document production to total nanotechnology document production.