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A Study on Technology Forecasting based on Co-occurrence Network of Keyword in Multidisciplinary Journals
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 Title & Authors
A Study on Technology Forecasting based on Co-occurrence Network of Keyword in Multidisciplinary Journals
Kim, Hyunuk; Ahn, Sang-Jin; Jung, Woo-Sung;
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Keyword indexed in multidisciplinary journals show trends about science and technology innovation. Nature and Science were selected as multidisciplinary journals for our analysis. In order to reduce the effect of plurality of keyword, stemming algorithm were implemented. After this process, we fitted growth curve of keyword (stem) following bass model, which is a well-known model in diffusion process. Bass model is useful for expressing growth pattern by assuming innovative and imitative activities in innovation spreading. In addition, we construct keyword co-occurrence network and calculate network measures such as centrality indices and local clustering coefficient. Based on network metrics and yearly frequency of keyword, time series analysis was conducted for obtaining statistical causality between these measures. For some cases, local clustering coefficient seems to Granger-cause yearly frequency of keyword. We expect that local clustering coefficient could be a supportive indicator of emerging science and technology.
Complex Systems;Technology Forecasting;Keyword Analysis;Growth Pattern;Time-Series Analysis;
 Cited by
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