Scientific Map Analysis and Visualization of Articles Published In the Journal of Research in School and Virtual Learning Using the Social Networks Analysis Approach

Document Type : Research Paper

Authors

1 Assistant Professor, Department of Computer and Information Technology Engineering, Payam-e-Noor University, Tehran, Iran .

2 Assistant Professor, Department of Computer and Information Technology Engineering, Payam-e-Noor University, Tehran, Iran.

3 PhD Student, Department of Information Technology Engineering, Tarbiat Modares University, Tehran, Iran.

Abstract

Purpose: Today, with the advancement of communication technologies, particularly the Internet, we are witnessing the generation of a vast amount of information. In academic research, it is crucial to identify the most frequently studied topics and challenges in each field, as well as to determine their significance. One way to evaluate scientific research in any field is by analyzing its scientific map. One of the most effective methods for visualizing and analyzing a scientific map is to utilize network analysis approaches. This technique can effectively demonstrate the structure of scientific networks.
 
Methodology: In this study, we visualized and analyzed the scientific network of articles published in the journal "Research in School and Virtual Learning" using network and co-word analysis methods. A total of 227 articles were included in the analysis. The general research approach includes collecting and cleaning data, constructing matrices of scientific networks, and analyzing and evaluating the results. Various scientific networks of articles, including the co-authorship network, co-organization network, semantic network of articles, and co-occurrence network of words, have been analyzed. PHP language was used for data crawling and processing, while Python language and Gephi software were utilized for network-based analysis and visualization of different networks. In addition, a proposed approach based on the TF-IDF method has been used to calculate the adjacency matrices of each network. This approach includes ten steps. 1) Integrating the title, keywords, and abstract of each article.
 
Findings: The findings reveal the extent of semantic connection among the published articles in the semantic network. In order to plot and analyze the semantic network of articles, the semantic matrix is obtained by multiplying the word-article matrix with the article-word matrix. The final semantic graph was clustered using the Grivan-Newman algorithm. The top six communities were evaluated based on various metrics. Also, the results showed that there are few articles with high and low degrees, and they are mostly located in the middle of the distribution chart. Therefore, the semantic network of the articles can be classified as a free scale type. The results of the co-occurrence analysis of words show that satisfaction, psychology, and emotion have been addressed more frequently than other topics. The result of the co-authorship network analysis showed that it has a degree of 2.881. Each author has contributed to the writing of the article with three other authors. The average clustering coefficient of the authors in the co-authored network was 0.685. The network exhibited a compactness value of 0.936 and consisted of 83 communities. Additionally, the results showed that the majority of articles were written collaboratively by three authors, followed by four and five authors. The largest component of the co-authorship network of articles was also extracted. Also, the individual network of the top authors in the co-authorship network was drawn and analyzed up to a depth of 3. Personal networks describe a person's relationships in the network with other authors. The structural characteristics of individual networks determine many aspects of a person's cooperative behavior, including the willingness to cooperate and share resources. The analysis of the intra-university collaboration network showed that the researchers of Payam-e-Noor University had the highest number of intra-university collaborations, with 42 articles. After that, Islamic Azad University ranks next with 23 articles. The analysis of the co-university cooperation network showed that each educational institution has participated in the publication of articles with at least three other educational institutions.
 
Conclusion: Upon analyzing the word count, it is evident that the topics published in the journal exhibit a wide range of topic distribution. Also, the investigation of the authors' co-authorship network and its clustering showed that the authors of the articles were more inclined to form small scientific groups within their respective organizations, such as universities or research institutes. Also, Payam-e-Noor and Islamic Azad universities have the largest number of co-authored articles within the university. The co-authorship network of Payam-e-Noor University exhibits an interesting and significant structure, indicating a higher willingness to cooperate among university members compared to independent groups. While the authors at Azad University are more inclined to conduct research as independent groups.

Keywords

References

  1. احمدی، ح.، و عصاره، ف. (1396). مروری بر کارکردهای تحلیل هم‌واژگانی. فصلنامه مطالعات ملی کتابداری و سازمان‌دهی اطلاعات، 28 (1)، 125-145. https://www.sid.ir/paper/224340/fa

    امامی، م.، ریاحی‌نیا، ن.، و سهیلی، ف. (1399). ترسیم ساختار علمی حوزه تجهیزات پزشکی و آزمایشگاهی با استفاده از هم‌رخدادی واژگان. پژوهش‌نامه علم‌سنجی، 6 (1)، 41-56. https://doi.org/ 10.22070/rsci.2018.696

    حاضری، ا.، ملکی‌زاده، ف.، و بیک خورمیزی، ف. (1395). تحلیل هم‌واژگانی مقالات مستخرج از پایان‌نامه‌های کارشناسی ارشد علم اطلاعات و دانش‌شناسی، پژوهش‌نامه علم‌سنجی، 2 (4)، 49-62. https://doi.org/10.22070/rsci.2016.492

    حسن‌زاده دیزجی، ا.، عصاره، ف.، توکلی فراش، ل.، و اسمعیل پونکی، ا. (1401). تحلیل ساختار شبکه اجتماعی هم‌نویسندگی و هم‌واژگانی پژوهشگران ایرانی حوزۀ کیفیت زندگی با استفاده از شاخص‌های تحلیل شبکه اجتماعی. پژوهش‌نامه علم‌سنجی، 15 (8)، 123-146.

    https://doi.org/10.22070/rsci.2020.5766.1425

    خرازی، ک. (1385). یادگیری در رویکرد شناختی. تازه‌های علوم شناختی، 8 ،4 (32)‌، 86-89. https://www.sid.ir/paper/445696/fa

    رجب‌زاده، س.، اکرامی، م.، سهیلی، ف.، و ملکی، ح. (1398). ساختار فکری حوزه مطالعات آموزش از دور بر اساس تحلیل هم‌استنادی. پژوهش در یادگیری آموزشگاهی و مجازی، 6 ، 4‌، پیاپی 24 ، 121-107. https://doi.org/ 10.30473/etl.2019.5958

    سهیلی، ف.، و عصاره، ف. (1392). بررسی تراکم و اندازه شبکه اجتماعی موجود در شبکه هم‌نویسندگی مجلات علم اطلاعات. پژوهشنامه پردازش و مدیریت اطلاعات، 29 (2)، 351-372. https://doi.org/10.35050/JIPM010.2014.038

    صدیقی، م. (1393). بررسی کاربرد روش تحلیل هم‌رخدادی واژگان در ترسیم ساختار حوزه‌های علمی (مطالعه موردی: حوزه اطلاع‌سنجی)، پردازش و مدیریت اطلاعات (علوم و فناوری اطلاعات)، 30 (2)، 393-373. https://doi.org/10.35050/JIPM010.2015.040

    عدلی، ف.، لشگری، م.، و شیری، م. (1400). مطالعه علم‌سنجی فرایند پژوهش در مدیریت دانش و ارتباط مفهومی آن با حوزه آموزش. فصلنامه بازیابی دانش و نظام‌های معنایی، 28 (8)، 1-19. https://doi.org/10.22054/jks.2020.54938.1361

    عصاره، ف.، و بابایی، ک. (1393). شبکه هم‌نویسندگی مقالات منتشرشده در فصلنامه روان‌شناسی افراد استثنایی دانشگاه علامه طباطبایی و فصلنامه کودکان استثنایی پژوهشکده استثنایی. مطالعات دانش‌شناسی، 1 (1)، 1-17. http://ensani.ir/fa/article/386729

    عصاره، ف.، صراطی شیرازی، م.، و خادمی، ر. (1393). بررسی شبکه هم‌تألیفی پژوهشگران ایران در حوزه داروشناسی و داروسازی در پایگاه وب آو ساینس 2000-2012، مدیریت سلامت، 17 (56)، 45-33. https://jha.iums.ac.ir/article-1-1481-fa.html

    علیپور، ا.، و شالباف، ع. (1387). اخلاق آموزش مجازی،  اخلاق در علوم و فناوری، 1 (2)، 33-50. https://www.sid.ir/paper/122645/fa

    فهیمی‌فر، س.، و سهلی، ف. (1394). بررسی شبکه هم‌تألیفی مجلات علمی پژوهشی فارسی حوزه علم اطلاعات و دانش‌شناسی. تحقیقات اطلاع‌رسانی و کتابخانه‌های عمومی، ۲۱ (۱)، 127-151. https://doi.org/20.1001.1.26455730.1394.21.1.3

    کلبعلی، م. (1397). کاربرد فناوری‌های نوین در آموزش. اولین کنفرانس ملی یافته‌های نویین حوزه یاددهی و یادگیری، انجمن مطالعات برنامه درسی ایران (1)، 86-89. https://www.sid.ir/paper/899035/fa

    مکی‌زاده، ف.، و حاضری، ا. (1396). ترسیم نقشه مقالات مرتبط با اعتیاد با استفاده از تحلیل شبکه‌های اجتماعی در پایگاه مدلاین، فصلنامه علمی اعتیادپژوهی، 11 (41)، 65-84. http://etiadpajohi.ir/article-1-1133-fa.html

    نوچه ن، حمیدرضا.، شمس مورکانی، غ.، و قانعی‌راد، م.ا. (1397). تحلیل شبکه هم‌نویسندگی مقالات خارجی اعضای هیئت علمی رشته علوم‌تربیتی، پژوهش‌نامه علم‌سنجی، 4 (2)، 33-56. https://doi.org/10.22070/RSCI.2017.563

     

     

    Adliy, F., Lashgari, M., & Shiirii, M. (2021). Scientometric Study of the Research Process in Knowledge Management and its Conceptual Relationship with Education. Knowledge Retrieval and Semantic Systems, 8(28), 1-20. https://doi.org/10.22054/jks.2020.54938.1361 [In Persian].

    Ahmadi, H., & Osareh, F. (2017). Co-word analysis concept, definition and application. Librarianship and Information Organization Studies, 28(1), 125-145. https://www.sid.ir/paper/224340/fa [In Persian].

    Alavi, M., & Lajevardy, S. A. (2020). The Co-authorship Network of Published Articles in Conferences on Web Research Based on Social Network Analysis. International Journal of Web Research, 3(2), 9-15. https://doi.org/10.22133/ijwr.2021.261519.1080

    Albert, R., & Barabási, A. L. (2002). Statistical mechanics of complex networks. Reviews of modern physics, 74(1), 47. https://doi.org/10.1103/RevModPhys.74.47

    Alcaide–Muñoz, L., Rodríguez–Bolívar, M. P., Cobo, M. J., & Herrera–Viedma, E. (2017). Analysing the scientific evolution of e-Government using a science mapping approach. Government information quarterly, 34(3), 545-555. https://doi.org/10.1016/j.giq.2017.05.002

    Alipour, A & Shalbaf, O. (2008), Ethics in e-learning, Ethics in Science and Technology, 1(2), 33-50. https://www.sid.ir/paper/122645/fa [In Persian].

    Arnaboldi, V., Conti, M., La Gala, M., Passarella, A., & Pezzoni, F. (2016). Ego network structure in online social networks and its impact on information diffusion. Computer Communications, 76, 26-41.  https://doi.org/10.1016/j.comcom.2015.09.028

    Arnaboldi, V., Conti, M., Passarella, A., & Dunbar, R. I. (2017). Online social networks and information diffusion: The role of ego networks. Online Social Networks and Media, 1, 44-55. http://dx.doi.org/10.1016/j.osnem.2017.04.001

    Assefa, S. G., & Rorissa, A. (2013). A bibliometric mapping of the structure of STEM education using co‐word analysis. Journal of the American Society for Information Science and Technology, 64(12), 2513-2536. https://doi.org/ 10.1002/asi.22917

    Borgatti, S. P. (2005). Centrality and network flow. Social networks, 27(1), 55-71. http://dx.doi.org/10.1016/j.socnet.2004.11.008

    1. J. Watts & Steven Strogatz (June 1998). "Collective dynamics of 'small-world' networks". Nature, 393 (6684), 440–442. https://doi.org/10.1038/30918

    Dino, H., Yu, S., Wan, L., Wang, M., Zhang, K., Guo, H., & Hussain, I. (2020). Detecting leaders and key members of scientific teams in co-authorship networks. Computers & Electrical Engineering, 85, 106703. https://doi.org/10.1016/j.compeleceng.2020.106703

    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), (Spring & Summer), 41-56. https://doi.org/10.22070/rsci.2018.696 [In Persian].

    Fahimifar, S., & Sahli, F. (2015). Co-authorship network in scientific knowledge and information science persian journals. Research on Information Science and Public Libraries. 1(21), 151-127. https://doi.org/ 20.1001.1.26455730.1394.21.1.3.7  [In Persian].

    Freeman, L. C. (1977). A set of measures of centrality based on betweenness. Sociometry, 35-41. https://doi.org/10.2307/3033543

    Hassanzadeh Dizaji, E., Osareh, F., Tavakoli Farrash, L., & Esmaeil Pounaki, E. (2022). Co-authorship and Co-occurrence Network Structure Analysis of Iranian Researchers on Quality of Life Using Social Networks Analysis. Scientometrics Research Journal, 8(Issue 1, spring & summer), 123-146. https://doi.org/10.22070/rsci.2020.5766.1425 [In Persian].

    Hazeri, A., Makkizadeh, F., & Beyk Khormizi, F. (2016). The Co-word Analysis of Papers Extracted from the Information Science and Knowledge Studies Master Theses. Scientometrics Research Journal, 2 (2), (Autumn & Winter), 49-62. https://doi.org/10.22070/rsci.2016.492 [In Persian].

    Higaki, A., Uetani, T., Ikeda, S., & Yamaguchi, O. (2020). Co-authorship network analysis in cardiovascular research utilizing machine learning (2009–2019). International Journal of Medical Informatics, 143, 104274. https://doi.org/10.1016/j.ijmedinf.2020.104274

    Jacomy, M., Venturini, T., Heymann, S., & Bastian, M. (2014). ForceAtlas2, a continuous graph layout algorithm for handy network visualization designed for the Gephi software. PloS one, 9(6), e98679. https://doi.org/ 10.1371/journal.pone.0098679

    Jin, T., Wu, Q., Ou, X., & Yu, J. (2021). Community detection and co-author recommendation in co-author networks. International Journal of Machine Learning and Cybernetics, 12(2), 597-609. https://doi.org/ 10.1007/s13042-020-01190-8

    Kalbali, M. (2017). Application of new technologies in education, [In Conference on New Teaching-Learning Findings in Elementary School], (1), 86-89. https://www.sid.ir/paper/899035/fa [In Persian].

    Khalagi, K., Mansourzadeh, M. J., Aletaha, A., Yarmohammadi, H., Atlasi, R., Banar, S., Fahimfar, N., Hajipour, F., Sanjari, M., & Larijani, B. (2021). Co-authorship network analysis of Iranian researchers on osteoporosis. Archives of osteoporosis, 16(1), 1-12.  https://doi.org/10.1007/s11657-021-00914-9

    Khan, F. M., & Gupta, Y. (2021). A bibliometric analysis of mobile learning in the education sector. Interactive Technology and Smart Education. https://doi.org/10.1108/ITSE-03-2021-0048

    Kharrazi, K. (2007). Learning in a cognitive approach, Advances in Cognitive Sciences, 8(4), 86-89. https://www.sid.ir/paper/445696/fa [In Persian].

    Khasseh, A. A., Amiri, M. R., & Sadeghi, A. (2021). Topic analysis of nursing research using co-word analysis. Iranian Journal of Nursing and Midwifery Research, 26(5), 417. https://doi.org/10.4103/ijnmr.IJNMR_41_20

    Kumar, S. (2015), "Co-authorship networks: a review of the literature", Aslib Journal of Information Management, Vol. 67, No. 1, 55-73. https://doi.org/10.1108/AJIM-09-2014-0116

    Leydesdorff, L., & Milojević, S. (2012). Scientometrics. arXiv preprint arXiv:1.208,4566. https://doi.org/10.48550/arXiv.1208.4566

    Li, Y., Zhang, D., Luo, P., & Jiang, J. (2017). Interpreting the formation of co-author networks via utility analysis. Information Processing & Management, 53(3), 624-639. https://doi.org/10.1016/j.ipm.2016.12.007

    Liu, C., Liu, Z., Zhang, Z., Li, Y., Fang, R., Li, F., & Zhang, J. (2020). A Scientometric analysis and visualization of research on Parkinson's disease associated with pesticide exposure. Frontiers in Public Health, 8, 91. https://doi.org/10.3389/fpubh.2020.00091

    Makkizadeh, F., Hazeri, A. (2017).The map of articles related to addiction using social network analysis in Medline database,  Scientific Quarterly of Research on Addiction, 11(41), 65-84. http://etiadpajohi.ir/article-1-1133-fa.html [In Persian].

    Maltseva, D., & Batagelj, V. (2019). Social network analysis as a field of invasions: bibliographic approach to study SNA development. Scientometrics, 121(2), 1085-1128. https://doi.org//10.1007/s11192-019-03193-x

    Millington, T., & Luz, S. (2021). Analysis and classification of word co-occurrence networks from Alzheimer’s patients and controls. Frontiers in Computer Science, 3, 649508. https://doi.org/10.3389/fcomp.2021.649508

    Newman, M. E. (2004). Coauthorship networks and patterns of scientific collaboration. In Proceedings of the national academy of sciences, 101(suppl_1), 5200-5205. https://doi.org/10.1073/pnas.0307545100

    Newman, M. E. (2005). Power laws, Pareto distributions and Zipf's law. Contemporary physics, 46(5), 323-351. https://doi.org/10.1080/00107510500052444

    Nishavathi, E., & Jeyshankar, R. (2020). A scientometric social network analysis of international collaborative publications of all india institute of medical sciences, India. Journal of Information Science Theory and Practice, 8(3), 64-76. https://doi.org/10.1633/JISTaP.2020.8.3.5

    Nocheh Nasar, H., Shams Mourkani, G., & Ghanei Rad, M. A. (2018). Social Network Analysis of Co-Authorship of Faculty Members in Science Education Based on their Foreign Articles. Scientometrics Research Journal, 4,(2), (Autumn & Winter), 33-56. ‌https://doi.org/ 10.22070/rsci.2017.563 [In Persian].

    Osareh, F., & Baba'i, K. (2014). The Co-Authorship Networks of Published Articles in the Journal of Psychology of Exceptional Individuals Allameh Tabataba'i University and Journal of Exceptional Children. Knowledge Retrieval and Semantic Systems, 1(1), 1-17. https://doi.org/10.22054/jks.2014.244 [In Persian].

    Osareh, F., Serati Shirazi, M., & Khademi R.(2014). A Survey on Co-authorship Network of Iranian Researchers in the field of Pharmacy and Pharmacology in Web of Science during 2000-2012, Journal of health management and Informatics, 17 (56), 33-45. https://jha.iums.ac.ir/article-1-1481-fa.html [In Persian].

    Rajabzade, S., Ekrami, M., Soheili, F., & Maleki, H. (2019). Intellectual Structure of Distance Education Domain by Co-Citation Analyses. Research in School and Virtual Learning, 6(4), 107-121. https://doi.org/10.30473/etl.2019.5958 [In Persian].

    Rashid, S., Rehman, S. U., Ashiq, M., & Khattak, A. (2021). A scientometric analysis of forty-three years of research in social support in education (1977–2020). Education Sciences, 11(4), 149. https://doi.org/ 10.3390/educsci11040149

    Robertson, S. (2004). Understanding inverse document frequency: on theoretical arguments for IDF. Journal of documentation. https://doi.org/10.1108/00220410410560582

    Sampaio, R. B., Fonseca, M. V. d. A., & Zicker, F. (2016). Co-authorship network analysis in health research: method and potential use. Health research policy and systems, 14(1), 1-10. https://doi.org/0.1186/s12961-016-0104-5

    Schaeffer, S. E. (2007). Graph clustering. Computer science review, 1(1), 27-64.  https://doi.org/10.1016/j.cosrev.2007.05.001

    Sedighi, M. (2015). Using of co-word analysis method in mapping of the structure of scientific fields (case study: The field of Informetrics). Iranian Journal of Information Processing and Management, 30(2), 373-396.  https://doi.org/10.35050/JIPM010.2015.040 [In Persian].

    Soheili, F., & Osareh, F. (2014). A Survey on Density and Size of Co-authorship Networks in Information Science Journals. Iranian Journal of Information Processing and Management, 29(2), 351-372. https://doi.org/10.35050/JIPM010.2014.038 [In Persian].

    Xu, G., Zhang, Y., & Li, L. (2010). Web mining and social networking: techniques and applications‌, Vol. 6, Springer Science & Business Media. https://books.google.com/books

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