Using text mining techniques for identifying research gaps and priorities: a case study of the environmental science in Iran

Mohammad Rabiei (), Seyyed-Mahdi Hosseini-Motlagh () and Abdorrahman Haeri ()
Additional contact information
Mohammad Rabiei: Iranian Research Institute for Information Science and Technology (IranDoc)
Seyyed-Mahdi Hosseini-Motlagh: Iran University of Science and Technology (IUST)
Abdorrahman Haeri: Iran University of Science and Technology (IUST)

Scientometrics, 2017, vol. 110, issue 2, No 13, 815-842

Abstract: Abstract This study aims to observe the researchers’ behavior in Iranian scientific databases to determine the research gaps and priorities in their field of research. Text mining and natural language processing techniques were used to identify what researchers are looking for and to analyze existing research works. In this paper, the information about the behavior of researchers who work in the field of environmental science and existing research works in the Iranian scientific database are processed. The search trends in all areas are evaluated by analyzing the users’ search data. The trend analysis indicates that in the period of February 2013 to July 2015, the growth of the researchers’ requests in some domains of the environment such as Industry, Training, Assessment, Material, Water and Pollution was 1.5 up to 2 times more than the overall requests. A Combination of the trend analysis and clustering of queries led to shaping four priority zones. Then, the research priorities for each environmental research area were determined. The results show that Training, Pollution, Rangeland, Management and Law are those domains in the environmental research which have the most research gaps in Iran, but there are enough research in Forest, Soil and Industry domains. At the end, we describe the steps for the implementation of a decision support system in environmental research management. Researchers, managers and policy makers can use this proposed “research demand and supply monitoring” system or RDSM to make appropriate decisions and allocate their resources more efficiently.

Keywords: Research priority; Research gap; Text mining; Environment studies; Researchers’ behavior analysis (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://link.springer.com/10.1007/s11192-016-2195-8 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:scient:v:110:y:2017:i:2:d:10.1007_s11192-016-2195-8

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11192

DOI: 10.1007/s11192-016-2195-8

Access Statistics for this article

Scientometrics is currently edited by Wolfgang Glänzel

More articles in Scientometrics from Springer, Akadémiai Kiadó
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().