Network Analysis of Green Technology using Keyword of Green Field

Abstract

In this study, the trend in green technology was observed and the domain of the green technology area that will be actively studied in the future was found by establishing knowledge map in green technology area and comparing and analyzing green technology information in Korea and overseas in time series. For the purpose of this study, network analysis was conducted for the keyword of green technology information provided by green technology information portal site (www.gtnet.go.kr) operated by Korea Institute of Science and Technology Information. Network analysis was conducted using keyword, and change of study subject was found by dividing the analysis result into periods. In the result of network analysis on top 100 keywords from total English keyword, it was found that renewable energy related areas such as solar energy and biomass had high centrality. When the main keyword trend by year was studied, centrality of solar cell, nanotechnology, smart grid, and fuel cell were found to increase, showing that research and development in generation and use of renewable energy are actively made.

Network Analysis on Green Technology in National Research and Development Projects in Korea

“…In the field of GT, several studies have used SNA, for example to observe specialized GTs, emerging GT fields, and clusters in GT in green-tech firms in San Francisco, New York City, and London [19]. Analysis of keywords to find trending topics in international GT has been used to forecast the future development and change in GT [46].…”

“…This study uses SNA that considers the co-occurrence of keywords [1,46] and centrality [43,45]. Co-occurrence analysis is used to generate a matrix of relationships between pairs of keywords for further network analysis and visualization.…”

“…Closeness centrality measures the inverse of the sum of the shortest distances between each node and every other node within the network [43]. A high value of closeness indicates that a node has close access directly and indirectly to other nodes; thus, this node can influence or monitor information flow between them [43,46].…”

“…Betweenness centrality represents the number of times that a node is on the shortest path that links two other nodes. Hence, high betweenness indicates that a node has high power to control the information flow through the network [43,45,46].…”