Improving the co-word analysis method based on semantic distance

Jia Feng, Yun Qiu Zhang () and Hao Zhang
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Jia Feng: Jilin University
Yun Qiu Zhang: Jilin University
Hao Zhang: Jilin University

Scientometrics, 2017, vol. 111, issue 3, No 13, 1531 pages

Abstract: Abstract We propose an improvement over the co-word analysis method based on semantic distance. This combines semantic distance measurements with concept matrices generated from ontologically based concept mapping. Our study suggests that the co-word analysis method based on semantic distance produces a preferable research situation in terms of matrix dimensions and clustering results. Despite this method’s displayed advantages, it has two limitations: first, it is highly dependent on domain ontology; second, its efficiency and accuracy during the concept mapping progress merit further study. Our method optimizes co-word matrix conditions in two aspects. First, by applying concept mapping within the labels of the co-word matrix, it combines words at the concept level to reduce matrix dimensions and create a concept matrix that contains more content. Second, it integrates the logical relationships and concept connotations among studied concepts into a co-word matrix and calculates the semantic distance between concepts based on domain ontology to create the semantic matrix.

Keywords: Co-word analysis; Semantic distance; Concept mapping; Semantic matrices (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (11)

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DOI: 10.1007/s11192-017-2286-1

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