Uluslararası Dergilerde Yayımlanan Türkiye Adresli Makalelerin Atıf Etkisini Artıran Faktörler

Yıl 2021, Cilt: 35 Sayı: 3, 388 - 409, 30.09.2021

Yaşar Tonta , Müge Akbulut

https://doi.org/10.24146/tk.933159

Cited By: 6

Öz

Amaç: Bu araştırmanın amacı Türkiye (TR) adresli uluslararası makalelerin atıf sayısını artıran faktörleri ortaya çıkarmaktır. Yöntem: 2006-2015 yıllarında yayımlanan yaklaşık 226 bin TR adresli makaleye ait bibliyografik veriler indirilmiş, bu verilerden olasılığa dayalı tabakalı %2’lik bir örneklem seçilmiş ve örneklemde yer alan makalelere ilişkin atıf sayısı, dergi etki faktörü, dergilerin çeyreklik değerleri, ortak yazar sayısı vb. gibi ilgili bilgiler çeşitli kaynaklardan elde edilmiştir. Daha sonra; makale, dergi, işbirliği, dizinleme, destek ve erişimle ilgili 19 bağımsız değişken saptanarak bu değişkenlerin TR adresli makalelerin atıf sayısı üzerindeki etkisi engel modeli (hurdle model) kullanılarak analiz edilmiştir. Bulgular: TR adresli makalelerin atıf sayısını artıran ve hiç atıf almayan makale sayısını azaltan en önemli faktörler, makalelerin yayımlandığı dergilerin beş yıllık dergi etki faktörü ve çeyreklik (Q1) değerleri ile makalelerin kaynakçalarında yer alan referans sayılarıdır. Yabancı ülkelerle işbirliği yapılarak yayımlanan makalelerin atıf sayısı daha yüksektir. Makalelerin konusu, desteklenip desteklenmemesi ve makaleye erişim yönteminin (açık/kapalı erişim) atıf sayısı üzerinde olumlu etkisi yoktur. Sonuç: Bu bulgular Türkiye adresli makalelerin bilimsel etkisini artırmak için dergi etki faktörü yüksek dergilerde yayımlanmasını özendiren, ama etki faktörü düşük dergilerde yayın yapılmasının da önüne geçen akademik yükseltme ve teşvik politikalarının geliştirilmesi gerektiğini göstermektedir. Özgünlük: Bu araştırma, engel modelini kullanarak makale, dergi, işbirliği, dizinleme, destek ve erişimle ilgili çok sayıda faktörün TR adresli makalelere yapılan atıf sayısına doğrudan etkisini araştıran ilk çalışmadır.
Anahtar Sözcükler: Atıf etkisi; dergi etki faktörü; akademik teşvik; engel modeli.

Anahtar Kelimeler

Atıf etkisi, dergi etki faktörü, akademik teşvik, engel modeli

Teşekkür

UBYT Programı ödeme verilerini sağlayan TÜBİTAK ULAKBİM Müdürü M. Mirat Satoğlu’ya teşekkür ederiz.

Factors Increasing the Citation Impact of Papers from Turkey Published in International Journals

Öz

Objective: This paper aims to find out the factors that are likely to increase the citation impact of Turkey-addressed international papers. Method: For this purpose, we downloaded bibliographic records of some 226,000 TR-addressed papers that were published between 2006 and 2015, therefrom selected a sample (2%) using stratified probabilistic sampling technique, and obtained relevant data from various sources such as the number of citations and co-authors, journal impact factors (JIF) and journal quartiles pertaining to each paper in the sample. We then identified 19 independent variables on article, journal, cooperation, support and access levels and analyzed the data using the hurdle model. Findings: The strongest factors increasing the number of citations of TR-addressed papers are five-year JIFs and journal quartiles (Q1) in which TR-addressed papers appeared and the number of references in papers’ reference lists. These factors also reduce the number of papers with zero citations. Papers published in cooperation with other countries collect higher numbers of citations. Factors such as the subjects of papers, whether papers received monetary support or not, and methods by which papers can be accessed (open or closed access) have no impact on the number of citations received. Implications: Findings indicate that academic promotion and support policies encouraging publishing in high impact journals while forestalling publishing in low impact journals should be developed in order to increase the scientific impact of TR-addressed papers. Originality: This is the first study using hurdle model to investigate the direct impact of several article, journal, collaboration, monetary support and access level explanatory variables on the number of citations that TR-addressed papers receive.

Anahtar Kelimeler

Citation impact, journal citation impact, academic incentives, hurdle model

Kaynakça

• Akçiğit, U. ve Özcan-Tok, E. (2020). Türkiye bilim raporu. TÜBA. http://www.tuba.gov.tr/tr/yayinlar/suresiz-yayinlar/raporlar/turkiye-bilim-raporu
• Al, U. (2012). Avrupa Birliği ülkeleri ve Türkiye’nin yayın ve atıf performansı. bilig, 62, 1-20. http://bilig.yesevi.edu.tr/yonetim/icerik/makaleler/1208-published.pdf
• Albarrán, P., Perianes-Rodrígues, A. ve Ruiz-Castillo, J. (2015). Differences in citation impact across countries. Journal of the Association for Information Science and Technology, 66(3), 512-525.
• Allik, J., Lauk, K. ve Realo, A. (2020). Factors predicting the scientific wealth of nations. Cross-Cultural Research, 54(4), 364-397. https://doi.org/10.1177/1069397120910982
• Article Influence. (2021). Clarivate: InCites help. https://incites.help.clarivate.com/Content/Indicators-Handbook/ih-article-influence.htm
• Baydemir, M. B. (2014). Lojistik regresyon analizi üzerine bir inceleme [Yayımlanmamış yüksek lisans tezi]. İnönü Üniversitesi. http://abakus.inonu.edu.tr/xmlui/bitstream/handle/11616/5650/Tez%20Dosyas%C4%B1.pdf?sequence=1&isAllowed=y
• Bornmann, L. ve Daniel, H. (2008). What do citation counts measure? A review of studies on citing behavior. Journal of Documentation, 64(1), 45-80. https://doi.org/10.1108/00220410810844150
• Bornmann, L., Wagner, C. ve Leydesdorff, L. (2018). The geography of references in elite articles: Which countries contribute to the archives of knowledge? PLoS ONE, 13(3), e0194805. https://doi.org/10.1371/journal.pone.0194805
• CiTO. (2018, 16 Şubat). The citation typing ontology. https://sparontologies.github.io/cito/current/cito.html
• Chen, C. (2012). Predictive effects of structural variation on citation counts. Journal of the American Society for Information Science and Technology, 63(3), 431-449. https://doi.org/10.1002/asi.21694
• Confraria, H., Godinho, M. M. ve Wang, L. (2017). Determinants of citation impact: A comparative analysis of the Global South versus the Global North. Research Evaluation, 46(1), 265-279. http://dx.doi.org/10.1016/j.respol.2016.11.004
• Desjardins, C. D. (2016). Modeling zero-inflated and overdispersed count data: An empirical study of school suspensions, The Journal of Experimental Education, 84(3), 449-472. https://doi.org/10.1080/00220973.2015.1054334
• Didegah, F. ve Thelwall, M. (2013a). Which factors help authors produce the highest impact research? Collaboration, journal and document properties. Journal of Informetrics, 7(4), 861-873. http://dx.doi.org/10.1016/j.joi.2013.08.006
• Didegah, F. ve Thelwall, M. (2013b). Determinants of research citation impact in nanoscience and nanotechnology. Journal of the American Society for Information Science and Technology, 64(5), 1055-1064. https://doi.org/10.1002/asi.22806
• Dinarcan, G. N. (2018). Sayma verisi için regresyon modelleri ve bir uygulama [Yayımlanmamış yüksek lisans tezi]. Hacettepe Üniversitesi. http://www.openaccess.hacettepe.edu.tr:8080/xmlui/bitstream/handle/11655/4613/10195911.pdf?sequence=4&isAllowed=y
• Fischer, I. ve Steiger, H-J. (2018). Dynamics of Journal Impact Factors and limits to their inflation. Journal of Scholarly Publishing, 50(1), 26-36. https://doi.org/10.3138/jsp.50.1.06
• Fronzetti Colladon, A., D’Angelo, C. A. ve Gloor, P. A. (2020). Predicting the future success of scientific publications through social network and semantic analysis. Scientometrics, 124, 357-377. https://doi.org/10.1007/s11192-020-03479-5
• Good, B., Vermeulen, N., Tiefenthaler, B. ve Arnold, E. (2015). Counting quality? The Czech performance-based research funding system. Research Evaluation, 24(2), 91-105. https://doi.org/10.1093/reseval/rvu035
• Gök, A., Rigby, J. ve Shapira, P. (2016). The impact of research funding on scientific outputs: Evidence from six smaller European countries. Journal of the Association for Information Science and Technology, 67(3), 715-730. https://doi.org/10.1002/asi.23406
• Hicks, D., Wouters, P., Waltman, L., de Rijcke, S. ve Rafols, I. (2015). Bibliometrics: The Leiden Manifesto for research metrics. Nature, 520(7548), 429-431. https://doi.org/10.1038/520429a
• Jackman, S., Tahk, A., Zeileis, A., Maimone, C., Fearon, J. ve Meers, Z. (2020). Package ‘pscl’. https://cran.r-project.org/web/packages/pscl/pscl.pdf
• Kamalski, J., Huggett, S., Kalinaki, E., Lan, G., Lau, G., Pan, L. ve Scheerooren, S. (2017). World of Research 2015: Revealing patterns and archetypes in scientific research. http://dlibra.umcs.lublin.pl/dlibra/docmetadata?id=26567&from=pubindex&dirids=12&lp=478
• Kleiber, C. ve Zeileis, A. (2016). Visualizing count data regressions using rootograms, The American Statistician, 70(3), 296-303. https://doi.org/10.1080/00031305.2016.1173590
• Kostoff, R. N. (1998). The use and misuse of citation analysis in research evaluation. Scientometrics, 43(1), 27-43. https://doi.org/10.1007/BF02458392
• Kostoff, R. N. (2007). The difference between highly and poorly cited medical articles in the journal Lancet. Scientometrics, 72, 513-520. https://doi.org/10.1007/s11192-007-1573-7
• Larivière, V., Kiermer, V., MacCallum, C. J., McNutt, M., Patterson, M., Pulverer, B., Swaminarhan, S., Taylor, S. ve Curry, S. (2016). A simple proposal for the publication of journal citation distributions. https://doi.org/10.1101/062109
• Leydesdorff, L., Bornmann, L. ve Wagner, C. S. (2019). The relative influences of government funding and international collaboration on citation impact. Journal of the Association for Information Science and Technology, 70(2), 198-201. https://doi.org/10.1002/asi.24109
• Lindsey, D. (1989). Using citation counts as a measure of quality in science measuring what’s measurable rather than what’s valid. Scientometrics, 15(3-4), 189-203. https://doi.org/10.1007/BF02017198
• Liu, F., Guo, W. ve Zuo, C. (2018). High impact factor journals have more publications than expected. Current Science, 114(5), 955-956. https://doi.org/10.18520/cs%2Fv114%2Fi05%2F955-956
• Liu, X. Z. ve Fang, H. (2020). A comparison among citation-based journal indicators and their relative changes with time. Journal of Informetrics, 14(1), 1-17. https://doi.org/10.1016/j.joi.2020.101007
• MacRoberts, M. H. ve MacRoberts, B. R. (1989). Problems of citation analysis: A critical review. Journal of the American Society for Information Science, 40(5), 342-349. https://doi.org/10.1002/(SICI)1097-4571(198909)40:5<342::AID-ASI7>3.0.CO;2-U
• MacRoberts, M. H. ve MacRoberts, B. R. (1996). Problems of citation analysis. Scientometrics, 36(3), 435-444. https://doi.org/10.1007/BF02129604
• MacRoberts, M. H. ve MacRoberts, B. R. (2018). The mismeasure of science: Citation analysis. Journal of the Association for Information Science and Technology, 69(3), 474-482. https://doi.org/10.1002/asi.23970
• Merton, R. K. (1968). The Matthew effect in science. Science, 159(3810), 56-63. https://doi.org/10.1126/science.159.3810.56
• Miranda, R. ve Garcia-Carpintero, E. (2019). Comparison of the share of documents and citations from different quartile journals in 25 research areas. Scientometrics, 121(1), 479-501. https://doi.org/10.1007/s11192-019-03210-z
• Muller, J. Z. (2019). Sayıların diktatörlüğü: Başarıyı rakamlarla ölçme saplantısı ve çözüm yolları (A. Kamacıoğlu, Çev.). The Kitap.
• Nicolaisen, J. ve Frandsen, T. F. (2019). Zero impact: A large-scale study of uncitedness. Scientometrics, 119(2), 1227-1254. https://doi.org/10.1007/s11192-019-03064-5
• Onodera, N. ve Yoshikane, F. (2015). Factors affecting citation rates of research articles. Journal of the Association for Information Science and Technology, 66(4), 739-764. https://doi.org/10.1002/asi.23209
• Orbay, K., Miranda, R. ve Orbay, M. (2020). Building journal impact factor quartile into the assessment of academic performance: A case study. Participatory Educational Research (PER), 7(2), 1-13. https://doi.org/10.17275/per.20.26.7.2
• Orbay, M., Karamustafaoğlu, O. ve Miranda, R. (2021). Analysis of the journal impact factor and related bibliometric indicators in education and educational research category. Education for Information, 37(3), 315-336. https://doi.org/10.3233/EFI-200442
• Pranckutė, R. (2021). Web of Science (WoS) and Scopus: The titans of bibliographic information in today’s academic world. Publications, 9(1), 1-59. https://doi.org/10.3390/publications9010012
• San Francisco Declaration on Research Assessment. (2012, 16 Aralık). What is DORA? http://ascb.org/dora
• Satoğlu, E. B., Balkış, G. ve Damar, H. (2021). TÜBİTAK araştırma geliştirme ve proje desteklerinin akademik araştırma faaliyetlerine olan etkisi. Yükseköğretim ve Bilim Dergisi, 11(1), 83-91. https://doi.org/10.5961/jhes.2021.431
• Seglen, P. O. (1997). Why the impact factor of journals should not be used for evaluating research. British Medical Journal, 314(7079), 498-502. https://doi.org/10.1136/bmj.314.7079.497
• Sivertsen, G. (2016). Patterns of internationalization and criteria for research assessment in social sciences and humanities. Scientometrics, 107(2), 357-368. https://doi.org/10.1007/s11192-016-1845-1
• Sivertsen, G. (2019). Understanding and evaluating research and scholarly publishing in the Social Sciences and Humanities (SSH). Data and Information Management, 3(2), 61-71. https://doi.org/10.2478/dim-2019-0008
• Tonta, Y. (2017). TÜBİTAK Türkiye Adresli Uluslararası Bilimsel Yayınları Teşvik (UBYT) programının değerlendirilmesi. TÜBİTAK ULAKBİM. http://yunus.hacettepe.edu.tr/~tonta/yayinlar/tonta-tubitak-ubyt-programinin-degerlendirilmesi.pdf
• Tonta, Y. (2018). Does monetary support increase the number of scientific papers? An interrupted time series analysis. Journal of Data and Information Science, 3(1), 19-39. https://doi.org/10.2478/jdis-2018-0002
• Tonta, Y. ve Akbulut, M. (2020). Does monetary support increase citation impact of scholarly papers? Scientometrics, 125(2), 1617-1641. https://doi.org/10.1007/s11192-020-03688-y
• Traag, V. A. (2021). Inferring the causal effect of journals on citations. Quantitative Science Studies, 1-9. https://doi.org/10.1162/qss_a_00128
• Tüzen, M. F. ve Erbaş, S. (2017). A comparison of count data models with an application to daily cigarette consumption of young persons. Communications in Statistics - Theory and Methods, 47(23), 5825-5844. https://doi.org/10.1080/03610926.2017.1402050
• Yan, E., Wu, C. ve Song, M. (2018). The funding factor: A cross-disciplinary examination of the association between research funding and citation impact. Scientometrics, 115, 369-384. https://doi.org/10.1007/s11192-017-2583-8
• Yurtsever, E., Gülgöz, S., Yedekçioğlu, Ö. A. ve Tonta, M. (2001). Sosyal Bilimler Atıf Dizini’nde (SSCI) Türkiye: 1970-1999. Türkiye Bilimler Akademisi.
• Yurtsever, E., Gülgöz, S., Yedekçioğlu, Ö. A. ve Tonta, M. (2002). Sağlık bilimleri, mühendislik ve temel bilimlerde Türkiye’nin uluslararası atıf dizinindeki yeri 1973-1999. Türkiye Bilimler Akademisi.
• Zeileis, A., Kleiber, C. ve Jackman, S. (2008). Regression models for count data in R. Journal of Statistical Software, 27(8), 1-25. https://doi.org/10.18637/jss.v027.i08