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Analysis and visualization of the Arabic Citation Index in the Web of Science platform

    Authors

    • Rasool Dehghanzad Shahreza 1
    • Jafar Ebadollah Amoqin 2
    • Iman Narimani 2

    1 Arabic literature language. university of qom. qom.iran

    2 Information science and epistemology. uneversity of qom.qom.iran

,

Document Type : علمی - پژوهشی

10.48308/jalc.2025.235017.1311
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Abstract

The present study tries to analyze and illustrate the indexed scientific productions related to Arabic literature researches in the Web of Science citation platform in order to help scientific policy making in this field. The current research is of an applied type and has been carried out using the methods of co-lexical analysis and network analysis. The research community includes all indexed information records related to Arabic literature in the Web of Science platform from the beginning to September 2023. A number of 881 information records, including articles, books, editor's remarks, conference abstracts, notes, etc., have been used in this research. The data analysis has been done using three softwares: Ves Viewer, Ucint and Babel Excel. Data analysis showed that keywords such as Arabic literature, translation, and modern Arabic literature were the most frequent keywords in the field of Arabic literature, respectively. Also, keywords such as: "Asian Studies-Literature", "Literary Theory & Criticism-Literature" and "History-Religion" have the most co-occurrence among the studied texts. The cluster analysis of the target keywords showed that this area includes 11 main clusters. The most important clusters based on synonym analysis showed that cluster one with 9 keywords is mainly related to the subject of Arabic literature, which has a stronger relationship with keywords such as "pedagogy" and "nahda".In terms of the amount of scientific productions in the field of Arabic literature, the United States of America is at the top with 198 degrees, and the United Kingdom ranks second with a difference of 134 degrees.
The present study tries to analyze and illustrate the indexed scientific productions related to Arabic literature researches in the Web of Science citation platform in order to help scientific policy making in this field. The current research is of an applied type and has been carried out using the methods of co-lexical analysis and network analysis. The research community includes all indexed information records related to Arabic literature in the Web of Science platform from the beginning to September 2023. A number of 881 information records, including articles, books, editor's remarks, conference abstracts, notes, etc., have been used in this research. The data analysis has been done using three softwares: Ves Viewer, Ucint and Babel Excel. Data analysis showed that keywords such as Arabic literature, translation, and modern Arabic literature were the most frequent keywords in the field of Arabic literature, respectively. Also, keywords such as: "Asian Studies-Literature", "Literary Theory & Criticism-Literature" and "History-Religion" have the most co-occurrence among the studied texts. The cluster analysis of the target keywords showed that this area includes 11 main clusters. The most important clusters based on synonym analysis showed that cluster one with 9 keywords is mainly related to the subject of Arabic literature, which has a stronger relationship with keywords such as "pedagogy" and "nahda".In terms of the amount of scientific productions in the field of Arabic literature, the United States of America is at the top with 198 degrees, and the United Kingdom ranks second with a difference of 134 degrees.
The present study tries to analyze and illustrate the indexed scientific productions related to Arabic literature researches in the Web of Science citation platform in order to help scientific policy making in this field. The current research is of an applied type and has been carried out using the methods of co-lexical analysis and network analysis. The research community includes all indexed information records related to Arabic literature in the Web of Science platform from the beginning to September 2023. A number of 881 information records, including articles, books, editor's remarks, conference abstracts, notes, etc., have been used in this research. The data analysis has been done using three softwares: Ves Viewer, Ucint and Babel Excel. Data analysis showed that keywords such as Arabic literature, translation, and modern Arabic literature were the most frequent keywords in the field of Arabic literature, respectively. Also, keywords such as: "Asian Studies-Literature", "Literary Theory & Criticism-Literature" and "History-Religion" have the most co-occurrence among the studied texts. The cluster analysis of the target keywords showed that this area includes 11 main clusters. The most important clusters based on synonym analysis showed that cluster one with 9 keywords is mainly related to the subject of Arabic literature, which has a stronger relationship with keywords such as "pedagogy" and "nahda".In terms of the amount of scientific productions in the field of Arabic literature, the United States of America is at the top with 198 degrees, and the United Kingdom ranks second with a difference of 134 degrees.

Keywords

  • Arabic literature
  • co-lexical analysis
  • co-occurrence of words
  • visualization of concepts
  • maps of science

Main Subjects

  • Arabic Literature Criticism
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References
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Davidescu, A.A., Hapau, R.G. and Manta, E.M. (2022), Impact of Crises on Capital Market Volatility: A Bibliometric Analysis, Grima, S., Özen, E. and Boz, H. (Ed.) The New Digital Era: Other Emerging Risks and Opportunities (Contemporary Studies in Economic and Financial Analysis, Vol. 109B), Emerald Publishing Limited, Bingley, pp. 21-53. https://doi.org/10.1108/S1569-37592022000109B003.
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Arabic Literature Bulletin
Volume 15, Issue 1 - Serial Number 28
January 2025
Pages 48-69
Files
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  • PDF 1.57 M
History
  • Receive Date: 08 March 2024
  • Revise Date: 17 June 2024
  • Accept Date: 20 December 2024
Share
How to cite
  • RIS
  • EndNote
  • Mendeley
  • BibTeX
  • APA
  • MLA
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Statistics
  • Article View: 177
  • PDF Download: 225

APA

Dehghanzad Shahreza, R. , Ebadollah Amoqin, J. and Narimani, I. (2024). Analysis and visualization of the Arabic Citation Index in the Web of Science platform. Arabic Literature Bulletin, 15(1), 48-69. doi: 10.48308/jalc.2025.235017.1311

MLA

Dehghanzad Shahreza, R. , , Ebadollah Amoqin, J. , and Narimani, I. . "Analysis and visualization of the Arabic Citation Index in the Web of Science platform", Arabic Literature Bulletin, 15, 1, 2024, 48-69. doi: 10.48308/jalc.2025.235017.1311

HARVARD

Dehghanzad Shahreza, R., Ebadollah Amoqin, J., Narimani, I. (2024). 'Analysis and visualization of the Arabic Citation Index in the Web of Science platform', Arabic Literature Bulletin, 15(1), pp. 48-69. doi: 10.48308/jalc.2025.235017.1311

CHICAGO

R. Dehghanzad Shahreza , J. Ebadollah Amoqin and I. Narimani, "Analysis and visualization of the Arabic Citation Index in the Web of Science platform," Arabic Literature Bulletin, 15 1 (2024): 48-69, doi: 10.48308/jalc.2025.235017.1311

VANCOUVER

Dehghanzad Shahreza, R., Ebadollah Amoqin, J., Narimani, I. Analysis and visualization of the Arabic Citation Index in the Web of Science platform. Arabic Literature Bulletin, 2024; 15(1): 48-69. doi: 10.48308/jalc.2025.235017.1311

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