December 6, 2025
Persian Gulf University
فارسی
mohammad bagher negahban
Academic Rank:
Associate professor
Address:
Persian gulf uni. faculty of humantis
Degree:
Ph.D in information science
Phone:
07731222044
Faculty:
Faculty of Humanities
E-mail:
bm [dot] negahban [at] gmail [dot] com
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Research
Title
Co-word Analysis of articles in related to kerman Agriculture in Islamic World Science Citation (ISCI) According to an Approach of Scientific map.
Type
Article
Keywords
كليدواژه ها تحليل هم واژگاني نقشه علمي نمايه استنادي علوم ايران كشاورزي كرمان
Journal
مدیریت اطلاعات
DOI
—
Researchers
Zohreh Soltani Zarandi (First researcher)
,
mohammad bagher negahban (Second researcher)
,
Fatemeh Makizadeh (Third researcher)
Abstract
Abstract The agricultural industry is a basic pillar for economic issues in the country which needs to related investment and should be noticed. This study was done with the aim of Co-Word Analysis of articles in related to Kerman Agriculture in Islamic World Science Citation (ISCI) According to an Approach of Scientific map. This research is a descriptive analytical study and systematically reviewed all Persian articles with agricultural subject in Islamic World Science Citation (ISCI). We focused on all studies which were done in Kerman province and published from 1999 to 2015.We used Co-word Analysis, hierarchical clustering and social network analysis by using Raver Matric software, SPSS, UC Net and Net drawer to design a related scientific map. The subjects were classified by Ward linkage method. The results showed a positive trend for articles related to the field of agriculture in Kerman and Most of articles related to agricultural issues in Kerman province were published in two Journals which were "Soil and Water Sciences" and "research and development". Bradford distribution determined 20 researchers who were on the top of the list in this field. Hierarchical charts were provided for related subjects and we had 36 clusters. Pistachio was the first subject for researches in Kerman. Our results showed that Co-word analysis could lead to acceptable analysis for research subjects, important terms and their relationships and also helps policy makers in order to increase the quantity and quality of scientific