Vol 6, No 3 (2015) > Industrial Engineering >

University Research Theme Mapping: A Co-word Analysis of Scientific Publications

Isti Surjandari, Arian Dhini, Nurman Wibisana, Esther Widya Impola Lumbantobing



There is a necessity
for a research centre to identify its main research theme and its subject
linkages. On the other hand, rapid growth in the number of scientific
publications has raised extensive data issues. Thus, it is difficult to detect
the main subject and its relationships using traditional methods.  Some quantitative methods in data mining have
been developed and applied to solve these problems. Co-word analysis, as one of
the most powerful tools in content analysis, is able to find the interrelationship
among research themes based on the co-occurrence frequency of word/phrase
pairs. As a result, the trend in research theme development is identifiable and
future research plans could be effectively determined. As a case study,
research publications from Universitas Indonesia (UI) academicians during the
last five years (2010-2015) were analyzed.
The data source for this study, are all those articles which have been indexed
in Scopus, EBSCO, JSTOR, and ProQuest. The study generated strategic diagrams which
show research themes of UI publications in
each year and over the last five years. The last five
years’ map shows that there are eleven main research themes in UI publications.
This result can be used as a base for evaluating the previous research themes
set by policy makers of UI.

Keywords: Big data analysis; Co-word analysis; Research theme mapping; Universitas Indonesia

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