Mapping the Knowledge Structure of Persian Research on Information Technology (2010-2019)

Document Type : Research Paper

Authors

1 Associate Professor, Department of Knowledge and Information Science, Payame Noor University, Tehran, Iran.

2 Associate Professor, Department of Knowledge and Information Science, Payame Noor University, Tehran, Iran .

3 M.A. in Knowledge and Information Science, Payame Noor University, Tehran, Iran.

Abstract

Purpose: One of the most important indicators of a country's development is its progress in scientific research across various fields and disciplines. Evaluating scientific output in different areas reveals the trajectory of scientific advancement within those fields. The analysis of co-occurring keywords and co-authorship, as key conceptual visualizations in scientometrics, is  widely used for mapping the network of scientific domains. Recent scientometric studies have extensively employed this approach to facilitate conceptual analysis. This study aimed to analyze and visualize the scientific landscape of Persian research in information technology (IT), as it is essential to understand the research profile of this significant scientific field. This analysis is based on articles indexed in the Iranian Science Citation Index (ISC) database over a decade, from 2010 to 2019.
Methodology: Taking a bibliometric and scientometric approach, the present study is an applied research effort that utilizes both co-authorship and co-word analysis, along with social network analysis. This scientometric investigation identifies and analyzes key bibliometric features of research on information technology published in Persian journals. These features include, among others, highly productive authors, influential authors, the most cited and referenced papers, authorship patterns, authorship networks, author centralities, frequently used keywords, co-occurring keyword pairs, and subject clusters. The statistical population comprised 2,107 articles indexed in the field of information technology within the Iranian Science Citation Index (ISC). Data were extracted from nine specialized journals as the Persian sources that are well-known in the field and have been indexed in the ISC database. A keyword search for the phrase "IT" in the title field of the article search page yielded 287 articles. To analyze, visualize, and summarize the data, the software packages and "Excel" were utilized.
Findings: The results of the study indicated that the average number of authors per article among the papers was 2.61. "Hamid Hassanpour, with 20 published articles, and "Mohammad Javad Valdan Zoj, with 19 published articles, were the leading authors in terms of article count (considered highly productive authors). In contrast, "Abolfazl Shahabadi" and "Manouchehr Manteghi, with 49 and 40 citations respectively, were recognized as the most cited authors (considered highly influential authors) in the field of Information Technology (IT). The average number of citations per article was less than one, specifically 0.95. Articles on "Organizational Agility" and "Open Innovation" were identified as the most cited works in this domain. Additionally, the average number of sources cited per article was 29.8. The number of contributions that produced articles accounted for 42.5 percent of all publications. Of these articles, 39.7 percent were authored by three co-authors. The largest co-authorship network comprised 35 individual authors. "Mohammad Javad Valdan Zoj, "Sepehr Ghazi Nouri, and "Maghsoud Amiri" were the leading authors in the field of Information Technology (IT) based on their degree, betweenness, and closeness centralities, respectively. The keywords “Information and Communication Technology”, “Information Technology”, and "Knowledge Management" were the three most frequently used terms in this field. The most common pair of co-words among the author-assigned keywords was "knowledge management - information technology, followed by  - information and communication technology, - information technology, technology - education. Clusters in the field of IT were illustrated using 104 high-frequency keywords that appeared at least six times. The clusters included "Genetic Algorithm, "Knowledge-Based Development, "Research and Innovation, "Human Resources Productivity, "Higher Education, "Electronic Development, and "Knowledge Management. The network revealed eight main clusters, with the largest cluster containing 32 keywords and the smallest consisting of four keywords. These eight clusters were named as follows:  with 32 keywords,  with 16 keywords,  with 14 keywords,  with 12 keywords,  with 10 keywords,  with four keywords.
Conclusion: In conclusion, there is a pressing need to focus more on the production of articles related to specialized topics within the field of information technology for subject integration. Particular emphasis should be placed on the quality of the content in these articles, as well as the necessity for increased participation of women in the creation of articles in the information technology sector.

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References

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