2017
DOI: 10.1016/j.ipm.2017.02.001
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Intellectual structure of knowledge in iMetrics: A co-word analysis

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Cited by 133 publications
(72 citation statements)
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“…Co-Word or Co-Occurrence) (Yang et al 2012;Hu & Zhang, 2015;Khasseh et al 2017) and they correlate with each other (Cho, 2014). Using co-word analysis a researcher can quantitatively determine the links between research themes in a scientific field (Ding et al, 2001;Khasseh et al, 2017;Ravikumar et al, 2015;Sedighi, 2016) detect its conceptual subdomains (I.E. In other words the more frequently the cooccurrences between these keywords occur the closer their relationship is (Yang et al, 2012).…”
Section: Co-word Analysismentioning
confidence: 99%
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“…Co-Word or Co-Occurrence) (Yang et al 2012;Hu & Zhang, 2015;Khasseh et al 2017) and they correlate with each other (Cho, 2014). Using co-word analysis a researcher can quantitatively determine the links between research themes in a scientific field (Ding et al, 2001;Khasseh et al, 2017;Ravikumar et al, 2015;Sedighi, 2016) detect its conceptual subdomains (I.E. In other words the more frequently the cooccurrences between these keywords occur the closer their relationship is (Yang et al, 2012).…”
Section: Co-word Analysismentioning
confidence: 99%
“…The frequency of the co-occurrence of keywords implies the strength of the relationship between them (Chen, Chen, Wu, Xie, & Li, 2016;Ding et al, 2001;Feng et al, 2017). Particular Topics or Themes) and its thematic evolution (Muñoz-Leiva, Viedmadel-Jesús, Sánchez-Fernández, & López-Herrera, 2012) and identify emerging and disappearing topics within the field (Bhattacharya & Basu, 1998;Chen et al, 2016;Khasseh et al, 2017). Using co-word analysis a researcher can quantitatively determine the links between research themes in a scientific field (Ding et al, 2001;Khasseh et al, 2017;Ravikumar et al, 2015;Sedighi, 2016) detect its conceptual subdomains (I.E.…”
Section: Co-word Analysismentioning
confidence: 99%
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