| Title of Article |
Analysis of Research Data in Information Science Using Topic Modeling Method |
| Date of Acceptance |
4 March 2021 |
| Journal |
| Title of Journal |
JOURNAL OF MEKONG SOCIETIES |
| Standard |
SCOPUS |
| Institute of Journal |
Center for Research on Plurality in the Mekong Region (CERP) Faculty of Humanities and Social Sciences, Khon Kaen University, |
| ISBN/ISSN |
|
| Volume |
17 |
| Issue |
1 |
| Month |
January-April |
| Year of Publication |
2021 |
| Page |
|
| Abstract |
Most of the research data in the present world are in digital forms, and thus necessitate
searching of high-efficiency tools that provide accessibility and understanding of such
data. As a result, the computerization technology based on natural language
processing with the capacity of topic extraction and categorization would enable us to
obtain new research topics and future research direction in the study fields. This
research was aimed at analyzing and categorizing information science research data
obtained from the journals listed in the international database from 2013 to 2019. The
reseach methodology applied was data analysis that was based on the Topic Modeling
method – the technique used in locating word groups or topics in a corpus that
contains complicated and difficult works. This method yields reliable and high-accuracy
outcomes. The analyzed data were drawn from the research articles published in
information science journals, the names of which are listed in the Scimago Journal &
Country Rank in 2013-2019. Only the journals in the Web of Science and the articles
written in English were included in this research. The 30,571 research articles obtained
from 677 volumes of 99 journals were analyzed by the Topic Modeling method and
assigned the topics by the experts in the field. The findings revealed that during the
past 7 years, there were 30 topics found in information science. The first 5 frequently
found topics were: Competency Development, Data Management, Social Media
Analytics, Public and Community Services, and Bioinformatics. Comparison with other
research data analyzed in the field of information science during the past 5 years using
other techniques showed clear differences and tendency of the research topics to
change. The results of this research greatly benefit the establishing of research
directions in the future. |
| Keyword |
Research data; Information science; Data analytics; Topic modeling |
| Author |
|
| Reviewing Status |
มีผู้ประเมินอิสระ |
| Status |
ได้รับการตอบรับให้ตีพิมพ์ |
| Level of Publication |
นานาชาติ |
| citation |
false |
| Part of thesis |
true |
| Attach file |
|
| Citation |
0
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Publication
Journal Publication
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