Bibliometric Analysis for Use of Time Series in Animal Science

Year 2023, Volume: 6 Issue: 6, 700 - 705, 01.11.2023

Esra Yavuz

https://doi.org/10.47115/bsagriculture.1376895

Abstract

In this study, bibliometric analysis was applied to time series, which has been widely used in animal science studies in recent years. In the method part of the study, a bibliometric analysis was carried out for time series commonly used in animal science studies. In the study is to determine the trends in recent years in the field of animal science, by examining 3895 studies with the term "time series" in the title of the article published within the scope of SCI-Expanded between 1980 and 2023, within the scope of bibliometric analysis. Statistical evaluations were calculated using the R software belonging to the "bibliometrix" package. All data were generated bibliographically from the WoS system in plain text format. Time series has been one of the most popular research areas due to its application in many different fields such as cell biology, plant sciences, zoology, animal science, etc. There are many authors' works in the field of time series. According to the analysis, a total of 3202 studies, such as articles, journals, books, etc. by 14154 authors, were published on time series in animal science. As a result of the analysis, in the 14154 authors, only 247 studies has been single authored documents of afromentioned topic. Time series in animal science examined within the scope of author’s collaboration that there were 0.275 authors per document. This study aims to conduct bibliometric analysis to determine the importance of time series in the field of agriculture, the number of publications by year, annual publication increase, and distribution by country and number of articles by keywords. The analysis results will be an important contribution to both readers and researchers.

Keywords

Animal sciences, Time series, Bibliometric

References

• Aria M, Cuccurullo C. 2017. Bibliometrix: An R-tool for comprehensive science mapping analysis. J Informet, 11(4): 959-975.
• Cui L, Tang W, Deng X, Jiang B. 2023. Farm Animal Welfare Is a Field of Interest in China: A bibliometric analysis based on CiteSpace. Animals, 13(19): 3143.
• Çanga D, Yavuz E, Ercan E. 2021. Prediction of egg weight using MARS data mining algorithm through R. Kahramanmaraş Sütçü İmam Üniv Tarım Doğa Derg, 24(1): 242-251.
• Derviş H. 2019. Bibliometric analysis using bibliometrix an R package. J Scientometric Res, 8(3): 156-160.
• Donthu N, Kumar S, Mukherjee D, Pandey N, Lim WM. 2021. How to conduct a bibliometric analysis: An overview and guidelines. J Busin Res, 133: 285-296.
• Freire R, Nicol CJ. 2019. A bibliometric analysis of past and emergent trends in animal welfare science. Animal Welf, 28(4): 465-485.
• Güneş SG, Gündoğdu K, Aksu HS. 2022. Bibliometric analysis of articles on volunteer tourism published in national peer-reviewed journals scanned by ULAKBİM. GSI J Serie A, 5(1): 1-15.
• Han J, Kang HJ, Kim M, Kwon GH. 2020. Mapping the intellectual structure of research on surgery with mixed reality: Bibliometric network analysis (2000–2019). J Biomed Inform, 109: 103516.
• Hotamışlı M, Erem I. 2014. Bibliometric analysis of articles published in the Journal of Accounting and Finance. Muhas Finans Derg, (63): 1-20.
• Karaokur ÖF, Kaya F, Yavuz E, Yenipınar A. 2019. Comparison of commonly used statistics package programs. BSJ Eng Sci, 2(1): 26-32.
• Mansiaux Y, Carrat F. 2012. Contribution of genome-wide association studies to scientific research: a bibliometric survey of the citation impacts of GWAS and candidate gene studies published during the same period and in the same journals. PLoS ONE, 7(12): e51408.
• Merigó JM, Yang JB. 2017. A bibliometric analysis of operations research and management science. Omega, 73: 37-48.
• Olfaz M, Tirink C, Önder H. 2019. Use of CART and CHAID algorithms in Karayaka sheep breeding. Kafkas Üniv Vet Fak Derg, 25(1): 105-110.
• Önder H, Tırınk C, 2022. Bibliometric Analysis for Genomic Selection Studies in Animal Science. J Instit Sci Technol, 12(3): 1849-1856.
• Öztürk N, Kurutkan MN. 2020. Examining quality management with bibliometric analysis method. J Innov Healthcare Pract, 1(1): 1-13.
• Persson O, Danell R, Schneider JW. 2009. How to use Bibexcel for various types of bibliometric analysis. Celebr Schol Commun Stud, 5: 9-24.
• R Core Team. 2020. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria.
• Sözeyatarlar M, Şahin M, Yavuz E. 2021. Statistical relations measures. J Univers Math, 4(2): 283-295.
• Tırınk C. 2022. Bibliometric Analysis for genome-wide association studies in animal science. BSJ Agri, 5(3): 234-239.
• Yavuz E, Şahin M. 2020. Survival analysis and application in livestock. BSJ Eng Sci, 3(1): 15-18.
• Yeksan Ö, Akbaba A. 2019. Bibliometric analysis of sustainable tourism articles. J Curr Tour Res, 3(2): 220-231.