APPLICATION OF MINING METHODS WITH A BIBLIOMETRIC PERSPECTIVE TO INTERNATIONAL REVIEWED PUBLICATIONS: THE CASE OF BALIKESİR UNIVERSITY

Year 2021, Volume: 5 Issue: 3, 143 - 176, 31.12.2021

Okan Koç Özlem Aydın

Abstract

The aim of this study is to perform bibliometric analysis of Balıkesir University's publications in Web of Science between 1994 and 2020 and to evaluate these publications with text mining methods. As a result of the evaluation, it will be emphasized how text mining methods can be used in priority field preferences. In this direction, a total of 4176 publications indexed between 1994-2020 in the Balıkesir University Web of Science bibliometric database were examined using the bibliometric analysis technique. Related publications; were evaluated according to the language of publication, the type of study, the countries with which they were published, the institutions they worked with, the most cited publications, the most published fields and authors. The findings obtained as a result of the research aim to reveal the international publication performance of Balıkesir University between 1994-2020.
Universityrelated publications are divided into four separate areas according to the Research Areas category in the WoS database. These fields are basic sciences, medicine and health sciences, engineering and architecture, and finally social sciences. The purpose of this distinction is to make both a general analysis of publications and a detailed analysis of these four subareas. Text mining analysis was performed using the keywords of the publications for both the entire dataset and the dataset divided into four. In the light of the findings obtained as a result of the research, what should be done to increase the number of international scientific publications was evaluated. In addition, the results of the text mining method are included. The analysis results were compared with the Wos categories information in the dataset. As a result of the comparison, detailed study areas were decided. Accordingly, it was concluded that the keywords that best represent the publications of Balıkesir University in WOS are included in the Wos Categories of 'biochemistry and molecular biology, chemistry, organic chemistry'. It has been observed that the words that best represent the field of basic sciences are in the Wos Categories of 'biochemistry and molecular biology, chemistry, organic chemistry'. In medicine and health sciences, these categories were determined as 'endocrinology and metabolism, cardiac and cardiovascular systems, biopsies, toxicology'. In social sciences, it has been observed as 'linguistics, education and educational research' categories.

Keywords

Balıkesir University, Bibliometric Analysis, Bibliometry, Web of Science, Text Mininig, TFIDF

ULUSLARARASI HAKEMLİ YAYINLARA BİBLİYOMETRİK BİR BAKIŞ İLE MADENCİLİĞİ YÖNTEMLERİNİN UYGULANMASI: BALIKESİR ÜNİVERSİTESİ ÖRNEĞİ

Abstract

Bu çalışmanın amacı, Balıkesir Üniversitesi’nin 1994- 2020 yılları arasında Web of Science' da yer alan yayınlarının, bibliyometrik analizini gerçekleştirmek ve bu yayınları metin madenciliği yöntemleri ile değerlendirmektir. Değerlendirme sonucunda metin madenciliği yöntemlerinin öncelikli alan tercihlerinde nasıl kullanılabileceği üzerinde durulacaktır. Bu doğrultuda Balıkesir Üniversitesi Web of Science bibliyometrik veri tabanında 1994-2020 yılları arasında indekslenen toplam 4176 yayın bibliyometrik analiz tekniği kullanılarak incelenmiştir. İlgili yayınlar; yayın diline, çalışmanın türüne, yayın yaptıkları ülkelere, çalıştıkları kurumlara, en çok atıf yapılan yayınlara, en çok yayın yapılan alanlara ve yazarlara göre değerlendirilmiştir. Araştırma sonucunda elde edilen bulgular, Balıkesir Üniversitesi'nin 1994-2020 yılları arasındaki uluslararası yayın performansını ortaya koymayı amaçlamaktadır.
Üniversiteye ilişkin yayınlar WoS veri tabanındaki Research Areas kategorisine göre dört ayrı alana ayrılmıştır. Bu alanlar temel bilimler, tıp ve sağlık bilimleri, mühendislik ve mimarlık son olarak sosyal bilimlerdir. Bu ayırımın amacı hem yayınların genel analizini hem de bu dört alt alanın ayrıntılı analizini yapmaktır. Araştırma sonucunda elde edilen bulgular ışığında; uluslararası bilimsel yayın sayısının artırılmasına yönelik yapılması gerekenler değerlendirilmiştir. Bununla birlikte metin madenciliği yönteminin sonuçlarına yer verilmiştir. Analiz sonuçları veri setinde bulunan WoS kategorisi bilgisi ile karşılaştırılmıştır. Karşılaştırma sonucu detaylı çalışma alanlarına karar verilmiştir. Buna göre Balıkesir Üniversitesinin WoS’ da yer alan yayınlarını en iyi temsil eden anahtar kelimelerin “biyokimya ve moleküler biyoloji, kimya, organik kimya olduğu sonucuna ulaşılmıştır. Tıp ve sağlık bilimlerinde ise bu kategoriler “endokrinoloji ve metabolizma, kardiyak ve kardiyovasküler sistemler, biyopsiler, toksikoloji” olarak tespit edilmiştir. Sosyal bilimlerde ise “dilbilim, eğitim ve eğitim araştırmaları” kategorileri olarak gözlenmiştir.

Keywords

Balıkesir Üniversitesi, Bibliyometrik Analiz, Bibliyometri, Web of Science, Metin Madenciliği, TFIDF

References

• Archambault, É., Vignola-Gagné, É., Côté, G., Larivière, V., & Gingras, Y. (2006). Benchmarking scientific output in the social sciences and humanities: The limits of existing databases. Scientometrics, 68(3), 329–342.
• Aydın, Ö. (2020). Mobbing İçerikli Yargı Kararlarının Makine Öğrenmesi Algoritmaları ile Sınıflandırılması. Balıkesir: Balıkesir Üniversitesi Fen Bilimleri Enstitüsü.
• Berry, M. W., ve Kogan, J. (2010). Text Mining: Applications and The-ory.
• Ergün, K. (2017). (Pusula Yayıncılık) 09 08, 2021 tarihinde http://kergun.baun.edu.tr/veri_madenciligi_hafta11.pdf adresinden alındı
• Feldman, R. ve Sanger, J. (2009). The Text Mining Handbook. Cambridge University Press.
• Gözen, E. (2020). Rekreasyon Bilim Alanının Geçmişten Günümüze Bib-liyometrik Analizi. Gaziantep University Journal of Social Sciences, 19(2). http://eds.b.ebscohost.com/eds/pdfviewer/pdfviewer?vid=0&sid=891e4cca-2114-4e0f-b8e4-ca8fd2db6607%40pdc-v-sessmgr01
• Hicks, D., & Wang, J. (2011). Coverage and overlap of the new social sciences and humanities journal lists. Journal of the American Society for Infor-mation Science and Technology, 62(2), 284–294. doi:10.1002/asi.21458.
• Huanh, C.-H., Yin, J., ve Hou , F. (2021). A Text Similarity Measurement Combining Word Semantic Information with TF-IDF Method. Chinese journal of computers, 5(34), 856—864.
• Koç, O. (2021). Web of Science Üzerinde İndekslenen Kadına Yönelik Şiddet Araştırmalarına Bibliyometrik Bir Bakış. İstanbul Üniversitesi Kadın Araştırmaları Dergisi, 21, 19-35. DOI: 10.26650/iukad.2020.22.002
• Kürklü, S. Biyoetik Konusunda Yapılan Araştırmaların Bibliyometrik Analizi; WOS Örneği. Türkiye Biyoetik Dergisi, 6 (3), 87-99. https://www.journalagent.com/tjob/pdfs/TJOB_6_3_87_99.pdf
• Larivière, V., Archambault, É., Gingras, Y., & Vignola-Gagné, É. (2006). The place of serials in referencing practices: Comparing natural sciences and en-gineering with social sciences and humanities. Journal of the American Society for Information Science and Technology, 57(8), 997–1004. doi:10.1002/asi.20349.
• Lohmann, S., Heimerl, F., Bopp, F., Burch, M., ve Ertl, T. (2015). Con-centri Cloud: Word Cloud Visualization for Multiple Text Documents. 2015 19th International Conference on Information Visualisation. Barcelona, Spain.
• Maharana, R. K. (2013). Bibliometric analysis of Orissa University of Ag-ricultural Technology’s research output as indexed in Scopus in 2008-2012. Chinese Librarianship: An International Electronic Journal, 36, 25-34. http://www.white-clouds.com/iclc/cliej/cl36maharana.pdf
• Maharana, R. K.; Sethi, B. B. (2013). A bibliometric analysis of the rese-arch output of Sambalpur University’s publication in ISI Web of Science during 2007-11. Library Philosophy and Practice (e-journal). Accessed online at: http://digitalcommons.unl.edu/libphilprac/926
• Mannila, H. (1996). Data mining: Machine learning, statistics, and databa-ses. Proceedings of 8th International Conference on Scientific and Statistical Data Base Management. Stockholm, Sweden.
• Mongeon, P., Paul-Hus, A. (2016). The journal coverage of Web of Sci-ence and Scopus: a comparative analysis. Scientometrics 106, 213–228. https://doi.org/10.1007/s11192-015-1765-5
• Nandi, A.; & Bandyopadhyay, A. K. (2009). Research contributions in chemistry at the University of Burdwan: An analytical study. Annals of Library and Information Studies, 56(3), 141-149. Nederhof, A. J. (2006). Bibliometric monitoring of research performance in the social sciences and the humanities: A review. Scientometrics, 66(1), 81–100. doi:10.1007/s11192-006-0007-2.
• Ohniwa, R. L., Hibino, A. ve Takeyasu, K. (2010). Trends in research fo-ci in life science fields over the last 30 years monitored by emerging topics. Sci-entometrics, 85 (1), 111-127.
• Porter, A. (2004). Technology futures analysis methods working group, technology futures analysis: Toward integration of the field and new methods. Technology Forecasting and Social Change, 71(3), 287–303.
• Rajman, M. and Vesely, M. ( 2004 ), " From text to knowledge: document processing and visualization: a text mining approach ", in Sirmakessis, D.S. (Ed.), Text Mining and its Applications , Studies in Fuzziness and Soft Compu-ting, Springer Berlin Heidelberg, pp. 7 – 24. https://doi.org/10.1007/978-3-540-45219-5_2
• Sevukan, R., & Sharma, J. (2008). Bibliometric analysis of research out-put of biotechnology faculties in some Indian central universities. DESIDOC Journal of Library & Information Technology, 28(6), 11. https://pdfs.semanticscholar.org/25ee/d2f920c76809e6f28a7a84c2a034e8b20fc2.pdf
• Shukla, N.; Merigo, J. M.; Lammers, T. ve Miranda, L. (2019). Half a century of computer methods and programs in biomedicine: A bibliometric analysis from 1970 to 2017. Computer Methods and Programs in Biomedicine. 183. https://doi.org/10.1016/j.cmpb.2019.105075
• Small, H. (2006). Tracking and predicting growth areas in science. Scien-tometrics, 68(3), 595- 610.
• Suk, F. M., Lien, G. S., Yu, T. C. ve Ho, Y. S. (2011). Global trends in Helicobacter pylori research from 1991 to 2008 analyzed with the Science Cita-tion Index Expanded. European Journal of Gastroenterology and Hepatology, 23 (4), 295-301.
• Tao, J., Qiu, D., Yang, F., & Duan, Z. (2020). A bibliometric analysis of human reliability research. Journal of Cleaner Production, 121041. https://doi.org/10.1016/j.jclepro.2020.121041 Van Raan, A. F. (2014). Advances in bibliometric analysis: research per-formance assessment and science mapping. Bibliometrics. Use and abuse in the review of research performance, 3, 17-28. https://portlandpress.com/DocumentLibrary/Umbrella/Wenner%20Gren/Vol%2087/WG_87_chapter%203.pdf
• Vargas-Quesada, B., De-Moya-Anegón, F., Chinchilla-Rodríguez, Z., Co-rera-Álvarez, E., & Guerrero-Bote, V. (2008). Evolución de la estructura ci-entífica española: ISI web of science 1990-2005. El Profesional De La Informa-ción, 17(1), 22-37. doi:http://dx.doi.org/10.3145/epi.2008.ene.03
• Yu, D., Xu, Z. & Wang, X. (2020). Bibliometric analysis of support vec-tor machines research trend: a case study in China. Int. J. Mach. Learn. & Cy-ber. 11, 715–728. https://doi.org/10.1007/s13042-019-01028-y