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Content analysis of documents using neural networks: A study of Antarctic science research articles published in international journals
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作者 dastidar Prabir G JHA, Deepak Kumal 《Advances in Polar Science》 2012年第1期41-46,共6页
Content analysis of scientific papers emanating from Antarctic science research during the 25 years period (1980-- 2004) has been carried out using neural network based algorithm-CATPAC. A total of 10 942 research a... Content analysis of scientific papers emanating from Antarctic science research during the 25 years period (1980-- 2004) has been carried out using neural network based algorithm-CATPAC. A total of 10 942 research articles published in Science Citation Indexed (SCI) journals were used for the study. Normalized co-word matrix from 35 most-used significant words was used to study the semantic association between the words. Structural Equivalence blocks were constructed from these 35 most-used words. Four-block model solution was found to be optimum. The density table was dichotomized using the mean density of the table to derive the binary matrix, which was used to construct the network map. Network maps represent the thematic character of the blocks. The blocks showed preferred connection in establishing semantic relationship with the blocks, characterizing thematic composition of Antarctic science research. The analysis has provided an analytical framework for carrying out studies on the con- tent of scientific articles. The paper has shown the utility of co-word analysis in highlighting the important areas of research in Antarctic science. 展开更多
关键词 ANTARCTICA content analysis thematic analysis SCIENTOMETRICS neural network CO-OCCURRENCE co-word social network analysis
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