Mapping and Analysis Knowledge Structure of Hawraman Research in Iran: A Co-word Analysis and Information Clustering

Ahmadi, Hamid and Bakhtiarian, Iraj Mapping and Analysis Knowledge Structure of Hawraman Research in Iran: A Co-word Analysis and Information Clustering. Journal of Knowledge-Research Studies, 2023, vol. 2, n. 3, pp. 31-49. [Journal article (Paginated)]

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English abstract

Purpose: The purpose of this research is to analyze the knowledge structure of Hawraman research in Iran. Methodology: This study employed content analysis techniques, specifically co-word analysis and information clustering. The research community encompassed all scientific outputs from the beginning until 2022. Findings: The findings indicate a significant growth in research on Hawraman over the past two decades, with over 15 geographical areas being studied. Co-word analysis revealed more than 1500 concepts or keywords mentioned, with "Hawraman," "Tourism," "local architecture," and "Hawrami dialect" being the most frequently used concepts. Notably, the conceptual pairs "Hawraman-tourist attractions," "Hawraman-history," and "Hawraman-Palangan" exhibited the highest co-occurrences. Additionally, clustering analysis uncovered 15 main clusters within the field's knowledge. Furthermore, the analysis of conceptual maps showed extensive relationships between concepts, indicating a dense network of interconnected ideas. Conclusion: The Hawraman region has gained substantial attention from researchers due to its unique environmental conditions and UNESCO registration. Consequently, there has been a surge in research, leading to the exploration of numerous concepts. This research provides a comprehensive overview of the current state of Hawraman research and sheds light on the key issues being investigated. Value: This study represents the first attempt at analyzing research data for an area in western Iran.

Persian abstract

هدف: هدف پژوهش حاضر تحلیل ساختار دانش حوزه هورامان­پژوهی در ایران است. روش پژوهش: این پژوهش از نوع تحلیل محتوا است که با فنون هم واژگانی و خوشه­بندی اطلاعات انجام شده است. جامعه پژوهش نیز شامل کلیه بروندادهای علمی از ابتدا تا سال 1401 است. یافته­ها: یافته‌ها حاکی از آن است در دو دهه اخیر پژوهش­ها در این حوزه رشد چشم‌گیری داشته است و بیش از 15 ناحیه جغرافیایی مورد پژوهش قرار گرفته است. نتایج مربوط به تحلیل هم واژگانی نشان داد بیش از 1500 مفهوم یا کلیدواژه مطرح شده و مفاهیم «هورامان»، «گردشگری»، «معماری بومی» و «گویش هورامی» بیشترین فراوانی را در بین کلیه مفاهیم داشته است. زوج­های مفهومی «هورامان-جاذبه­های گردشگری»، «هورامان- تاریخ» و «هورامان- پالنگان» بیشترین هم رخدادی داشته‌اند. نتایج خوشه­بندی نشان داد دانش این حوزه از 15 خوشه اصلی تشکیل‌شده است. تجزیه‌وتحلیل نقشه‌ها حاکی از آن است مفاهیم این حوزه روابط مفهومی زیادی باهم دارند. تمرکز شبکه مفهومی حوزه برابر با عدد 102/2 است که شبکه­ی نسبتاً متراکمی می‌باشد. نتیجه ­گیری: ناحیه هورامان به دلیل شرایط زیست‌محیطی آن موردتوجه پژوهشگران قرار گرفته است و ثبت این ناحیه در سازمان یونسکو بیشتر از گذشته آن را موردتوجه قرار داده و به همین دلیل مفاهیم زیادی در مورد آن موردپژوهش قرار گرفته است. نتیجه این پژوهش همچنین وضعیت پژوهش­های این ناحیه را ازلحاظ روابط مفهومی منعکس کرد و تصویر کلانی از مباحث مطرح‌شده در پژوهش­ها را ارائه داد. اصالت و ارزش: این پژوهش نخستین پژوهش برای تحلیل داده­های پژوهشی یک ناحیه در غرب ایران است.

Item type: Journal article (Paginated)
Keywords: Hawraman Research, Co-word Analysis, Information Clustering, Scientometrics, Scientific Maps
Subjects: B. Information use and sociology of information
B. Information use and sociology of information > BB. Bibliometric methods
Depositing user: Rasoul Zavaraqi
Date deposited: 16 May 2024 03:02
Last modified: 16 May 2024 03:02
URI: http://hdl.handle.net/10760/45769

References

Ahmadi, H. ,& Osareh, F. (2016). An Overview of the Functions of Co-word analysis. Librarianship And Information Organization Studies, 28 (1), 125-145. [In Persian].

Ahmadi, H., Salimi, A., & Zangishehei, A. (2013). clustering and knowledge map of scientific productions of comparative literature in Iran. Research in Comparative Literature, 3(11), 1-28.[In Persian].

Alzafari, K. (2017). Mapping the literature structure of ‘quality in higher education’using co-word analysis. Quality in HigHer education, 23(3), 264-282.‏ https://doi.org/ 10.1080/13538322.2017.1418607

Anthony, A. (2007, October). Data clustering with a relational push-pull model. In Seventh IEEE International Conference on Data Mining Workshops (ICDMW 2007) (pp. 189-194). IEEE.‏

Davari, M., Ziaie, S., & Gharebaghloo, V. (2022). The Intellectual Structure of Knowledge in the Field of the Digital Library: a Co-Word Study. Library and Information Science Research, 12(2), 29-53. doi: 10.22067/infosci.2022.68914.1013[In Persian].

De la Hoz-Correa, A., Muñoz-Leiva, F., & Bakucz, M. (2018). Past themes and future trends in medical tourism research: A co-word analysis. Tourism management, 65, 200-211.‏https://doi.org/ 10.1016/j.tourman.2017.10.001

Emami, M., Riahinia, N., & Soheili, F. (2020). Mapping the Scientific Structure of Medical and Laboratory Equipment with Using the Co-occurrence Analysis. Scientometrics Research Journal, 6(1), 41-56. doi: 10.22070/rsci.2018.696 [In Persian].

Geraei, E., Farshid, R., & Faraji, F. (2021). Co-word analysis in nursing science. Caspian Journal of Scientometrics, 8(1), 44-57.‏ URL: http:// Doi:10.22088/cjs.8.1.44 [In Persian].

Ghazizadeh, H., Soheili, F., & Khasseh, A. A. (2018). Mapping Knowledge Structure of Quran and Hadith Studies in Iran: A Co-Word Analysis. Scientometrics Research Journal, 4(2), 101-122. doi: 10.22070/rsci.2018.615.[In Persian]

Moomivand, H., Hasni Ahangar, M. R., Tahmasab Kazemi, B., Saleh Nejad, S. A., & kameli, B. (2022). Drawing and Creating the knowledge map of the field of commercialization based on the Co-word analysis of articles indexed in the Web Of Science. Organizational Knowledge Management,2(5), 77-110. 20.1001.1.26454262.1401.5.2.3.9 [In Persian].

Khoeini, S., Noruzi, A., Jozi, Z., & Mostafavi, I. (2022). Co-word Analysis of Scientific Outputs in the Field of Bibliotherapy in Web of Science. Caspian Journal of Scientometrics, 9(1), 13-28.‏ https://doi.org/ 10.22088/cjs.9.1.13[In Persian].

Leydesdorff L. (2010). Eugene Garfield and algorithmic historiography: co-word, co-authors, and journal Nams. Annals of Library and Information Studies, 57 (3),248-260.

Liu, G. Y., Hu, J. M., & Wang, H. L. (2012). A co-word analysis of digital library field in China. Scientometrics, 91(1), 203-217.‏ https://doi.org/10.1007/s11192-011-0586-4

Neville, J., Adler, M., & Jensen, D. (2003, August). Clustering relational data using attribute and link information. In Proceedings of the text mining and link analysis workshop, 18th international joint conference on artificial intelligence (pp. 9-15).‏

Osareh, F., Heydari, G., Zare Farashbandi, F., & Haji Zain Al Abdini, M. (2009). From bibliometrics to web metrics: An analysis of the basics, views, rules and indicators. Ketabdar. [In Persian]

Rahimi, S., Soheili, F., & Sharafi, N. (2022). Knowledge Structure of Iranian Higher Education Studies based on co-word Network Analysis in ISC Database. Journal of higher education curriculum studies, 12(24), 313-331. [In Persian].

Shen, L., Xiong, B., & Hu, J. (2017). Research status, hotspots and trends for information behavior in China using bibliometric and co-word analysis. Journal of Documentation, 73(4), 618-633.‏ https://doi.org/ 10.1108/JD-10-2016-0125

Sohaili, F., Khase, A., & Koranian, P. (2016). Map Intellectual Structure of Knowledge and Science in Iran based on Co-word Analysis. Information processing and management , 34 (4), 1905-1938. doi: 10.35050/JIPM010.2019.026. [In Persian]

Taşkın, Z. (2021). Forecasting the future of library and information science and its sub-fields. Scientometrics, 126(2), 1527-1551.‏ https://doi.org/ 10.1007/s11192-020-03800-2

Whittaker, J. (1989). Creativity and conformity in science: Titles, keywords and co-word analysis. Social Studies of Science, 19(3), 473-496.‏ http://dx.doi.org/10.1177/030631289019003004

Zhu, X., & Zhang, Y. (2020). Co-word analysis method based on meta-path of subject knowledge network. Scientometrics, 123(2), 753-766.‏ https://doi.org/ 10.1007/s11192-020-03400-


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