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“…For the detection of the clusters (called "communities," which can be interpreted as topics in the context of semantic analysis), we used the modularity (Q) value (Clauset et al 2004), employing the greedy algorithm featured in a previous study (Fortunato 2010). After creating the co-occurrence network, we digitized the reference density of each community obtained from the network based on the product of the text of respondents and the word frequency matrix, as implemented by Suga et al (1993). We then applied a multiple factor analysis and visualized the mutual correlation with the intensity of each topic (community) as a vector on the correlation circle.…”
Section: Workheetsmentioning
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“…For the detection of the clusters (called "communities," which can be interpreted as topics in the context of semantic analysis), we used the modularity (Q) value (Clauset et al 2004), employing the greedy algorithm featured in a previous study (Fortunato 2010). After creating the co-occurrence network, we digitized the reference density of each community obtained from the network based on the product of the text of respondents and the word frequency matrix, as implemented by Suga et al (1993). We then applied a multiple factor analysis and visualized the mutual correlation with the intensity of each topic (community) as a vector on the correlation circle.…”
Section: Workheetsmentioning