Turkiye Klinikleri Journal of Sports Sciences

.: ORIGINAL RESEARCH
A Bibliometric Analysis on Machine Learning in Sports Studies From 1999 to 2021
1999-2021 Yılları Arasında Yapılmış Spor Araştırmalarında Makine Öğrenmesi Üzerine Bir Bibliometrik Analiz
Halil Orbay ÇOBANOĞLUa, Eren AKDAĞb, Muhammed Akif KURTULUŞc
aDepartment of Coaching Education, Alanya Alaaddin Keykubat University Faculty of Sports Sciences, Antalya, Türkiye
bDepartment of Physical Education and Sports Teaching, Alanya Alaaddin Keykubat University Faculty of Sports Sciences, Antalya, Türkiye
cDepartment of Mathematics and Science Education, Alanya Alaaddin Keykubat University Faculty of Education, Antalya, Türkiye
Turkiye Klinikleri J Sports Sci. 2023;15(1):142-52
doi: 10.5336/sportsci.2022-93356
Article Language: EN
Full Text
ABSTRACT
 Objective: The aim of the research is to make a bibliometric analysis of articles published using machine learning-sports key concepts. For this purpose, 654 studies published in the sources scanned in the Web of Science Core Collection database between 1999-2021 will be examined bibliometrically and the trend in the last 23 years will be revealed. Material and Methods: The database was searched using the keywords 'machine learning' and 'sports' and the number of studies for years, the average number of citations per year, the journals and authors that published the most on this subject, the citation burst values of the authors, the countries and cooperation status of the responsible authors, the most the cited articles, word cloud and word tree map and conceptual structures were examined under their sub-titles. Results: According to the results obtained, it can be said that the interest in the subject has increased after 2014. The journal in which the articles on this subject were published the most was 'Sensors', and it was determined that Musa RM was the author who wrote the most articles. The most cited work was written by Li and Wu in 2010. Conclusion: In the articles written, it has been determined that Australia and the United Kingdom are the countries most open to cooperation, and the most used concepts in the keyword and title section are 'performance' and 'learning'. It is believed that the results obtained will shed light on researchers who want to conduct research on this subject.

Keywords: Machine learning; sports; bibliometric analysis; network analysis
ÖZET
 Amaç: Bu çalışmanın amacı, 'machine learning-sports' anahtar kavramları kullanılarak yayımlanan makalelerin bibliyometrik analizini yapmaktır. Bu amaç doğrultusunda 1999-2021 yılları arasında Web of Science Core Collection veri tabanında taranan kaynaklarda yayımlanan 654 çalışma bibliyometrik açıdan incelenerek son 23 yıldaki eğilim ortaya koyulacaktır. Gereç ve Yöntemler: Veri tabanında 'machine learning' ve 'sports' anahtar kavramı kullanılarak tarama gerçekleştirilmiş ve yıllara ilişkin çalışma sayısı, yıllık ortalama alıntı sayısı, bu konuda en çok yayın yapan dergiler ve yazarlar, yazarların atıf patlama değerleri, sorumlu yazarların ülkeleri ve iş birliği durumları, en çok atıf alan makaleler, kelime bulutu ve kelime ağacı yapıları ve kavramsal yapıları alt başlıklarında incelenmiştir. Bulgular: Elde edilen sonuçlara göre konuya olan ilginin 2014 yılından sonra arttığı söylenebilir. Bu konudaki makalelerin en fazla yayımlandığı dergi 'Sensors' olup, Musa RM'nin en fazla makale yazan yazar olduğu belirlenmiştir. En fazla atıfı alan çalışma 2010 yılında Li ve Wu tarafından yazılmıştır. Sonuç: Yazılan makalelerde Avustralya ve Birleşik Krallık'ın iş birliğine en açık ülkeler olduğu, anahtar kelime ve başlık kısmında en çok kullanılan kavramların 'performance' ve 'learning' olduğu tespit edilmiştir. Elde edilen sonuçların bu konuda araştırma yapmak isteyen araştırmacılara ışık tutacağına inanılmaktadır.

Anahtar Kelimeler: Makine öğrenmesi; spor; bibliometrik analiz; ağ analizi
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