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.
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Author’s contribution
JF proposed the research idea, planned and designed the outline, carried out the data collection and data analysis, and wrote the first draft. YQZ revised the plan and outline, joined discussion of the findings, and contributed to writing the paper and revising it after review. HZ joined discussion of the findings and contributed to writing the paper.
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Feng, J., Zhang, Y.Q. & Zhang, H. Improving the co-word analysis method based on semantic distance. Scientometrics 111, 1521–1531 (2017). https://doi.org/10.1007/s11192-017-2286-1
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DOI: https://doi.org/10.1007/s11192-017-2286-1