Türkiye’de yapay zekâ alanında yapılan çalışmaların bibliyometrik analizi

Year 2024, Volume: 27 Issue: 52, 387 - 407, 30.12.2024

Noyan Aydın

https://doi.org/10.31795/baunsobed.1545006

Abstract

Bu çalışma, Türkiye'de yapay zekâ alanında yapılmış araştırmalara ilişkin bir bibliyometrik analiz sunmaktadır. Böylece, alandaki temel eğilimler ve temalar, literatüre katkıda bulunmuş etkili yayınlar, üretken kişi ve kurumlar ile iş birliği ağları belirlenerek Türkiye’deki araştırmaların odağı ve gelişimi değerlendirilebilecektir. Çalışmada, yayın üretkenliği, ortak yazarlık kalıpları, anahtar kelime birlikteliği, atıf ağları ve tematik harita gibi bibliyometrik göstergeleri belirleyebilmek amacıyla Scopus veri tabanındaki 4.049 makalenin bibliyometrik verisi VOSviewer ve R yazılımları aracılığıyla görselleştirilerek analiz edilmiştir. Bulgular, özellikle son beş yılda Türkiye'de yapay zekâ alanındaki araştırma çıktısında önemli bir artış olduğunu göstermektedir. Öne çıkan temel araştırma alanları arasında makine öğrenimi, derin öğrenme ve sinir ağları ile bunlara yönelik algoritma ve uygulamalar yer almakta olup araştırmalardaki küresel eğilimleri de yansıtmaktadır. Erciyes, Eskişehir Osmangazi, Fırat, Ankara ve Yakın Doğu üniversiteleri ve ilgili akademisyenlerinin çalışmalarıyla literatüre katkı anlamında öne çıktıkları görülmektedir. Hem Scopus hem de WoS veri tabanında endekslenen ve etki faktörü yüksek olan dergilerdeki SCIE nitelikli yayın sayısındaki artış da bunu doğrulamaktadır. Anahtar kavramlara ait bulgular, karar destek sistemleri ve optimizasyon teknikleri gibi temaların ivme kazanarak odak noktası haline geldiği ve uygulamalı yapay zekâ araştırmaları ile yapay zekâ pratik uygulamalarına doğru bir yönelimi işaret etmektedir. Fen bilimleri, tıp ve matematik sahasındaki gelişmelere rağmen, sosyal bilimlerde yapay zekânın kullanımı ile açıklanabilir yapay zekâ ve yapay zekâ etiği gibi alt alanlardaki dikkate değer boşluklar da dolaylı olarak vurgulanmıştır.

Keywords

Bibliyometrik analiz, yapay zekâ, yz, üniversite, akademisyen

Ethical Statement

Çalışmada anket, mülakat, odak grup çalışması, gözlem, deney, görüşme teknikleri kullanılmaması, insan ve hayvanların (materyal/veriler dahil) deneysel ya da diğer bilimsel amaçlarla kullanılmaması ve kişisel verilerin korunması kanunu kapsamında olmaması sebebiyle etik kurul izni gerektirmeyen çalışmalar arasında yer almaktadır. Bu alanda yapılan araştırmanın herhangi bir kurum, kişi veya kuruluş ile herhangi bir çıkar çatışması yoktur.

Supporting Institution

yok

The bibliometric analysis of studies in the field of artificial intelligence in Türkiye

Abstract

This study presents a bibliometric analysis of research conducted in the field of artificial intelligence (AI) in Türkiye. By identifying key trends and themes, influential publications contributing to the literature, prolific individuals and institutions, and collaboration networks, the focus and development of research in Türkiye can be evaluated. The study has visualized and analyzed the bibliometric data of 4,049 articles from the Scopus database using VOSviewer and R software to determine bibliometric indicators such as publication productivity, co-authorship patterns, keyword co-occurrence, citation networks, and thematic maps. The findings have revealed a significant increase in research output in the field of artificial intelligence in Türkiye, particularly in the last five years. Prominent research areas include machine learning, deep learning, neural networks, and related algorithms and applications, reflecting global trends in research. Universities such as Erciyes, Eskişehir Osmangazi, Fırat, Ankara, and Near East, along with their respective academics, stand out in terms of their contributions to the literature. This is further supported by the increase in SCIE-quality publications in high-impact journals indexed in both the Scopus and WoS databases. Findings related to key concepts have indicated that themes such as decision support systems and optimization techniques are gaining momentum and becoming focal points, signaling a shift towards applied artificial intelligence research and practical applications of AI. Despite advancements in natural sciences, medicine, and mathematics, the study indirectly highlights notable gaps in subfields such as the use of AI in social sciences, explainable AI, and AI ethics.

Keywords

Bibliometric analysis, artificial intelligence, ai, university, academician

Ethical Statement

The study does not involve the use of survey, interview, focus group study, observation, experiment, or discussion techniques, nor does it include the experimental or other scientific use of humans or animals (including materials/data). Additionally, it does not fall under the scope of the Personal Data Protection Law, and therefore, it is classified among studies that do not require ethical committee approval. “The research conducted in this field has no conflict of interest with any institution, individual, or organization.”

Supporting Institution

there is no

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