Yapay Zekânın Sosyal ve Doğa Bilimleri Araştırmalarında Kullanımındaki Eğilimler

Year 2025, Volume: 4 Issue: 1, 100 - 132, 31.05.2025

Zahid Zufar At Thaariq , Ence Surahman Mohammad Sameer Khader Jaradat Irene Mega Mellyana

https://doi.org/10.58239/tamde.2025.01.006.x

Abstract

Bu makale, yapay zekânın (YZ) sosyal bilimler ve doğa bilimleri araştırmalarında kullanımındaki eğilimleri ele almaktadır. Giriş bölümünde, YZ'nin her iki alanda da geleneksel yöntemlerin sınırlamalarını aşmada ve doğa bilimlerinde veri analizini hızlandırmada önemli bir araç haline geldiği vurgulanmaktadır. Araştırma yöntemi olarak bibliyometrik analiz kullanılmış olup, veriler Google Scholar'dan sosyal ve doğa bilimlerinde YZ ile ilgili anahtar kelimeler aracılığıyla toplanmıştır. İçerik değerlendirme ve hariç tutma süreciyle uygun makaleler seçilmiş ve sonuçta 1.000 sosyal bilim yayını ile 999 doğa bilim yayını elde edilmiştir. Bu yayınlar VOSviewer ile daha ayrıntılı analiz edilmiştir. Araştırma bulgularına göre, sosyal bilimlerde YZ, özellikle yükseköğretim ve sosyal politika analizinde daha hızlı veri işleme yoluyla araştırma etkinliğini artırmak amacıyla yaygın olarak kullanılmaktadır. Ayrıca, sosyal bilimlerdeki YZ çalışmaları etik, düzenleme ve insan-YZ etkileşimi gibi alanlarda genişlemektedir. Doğa bilimlerinde ise YZ, kaynak yönetimi, çevre araştırmaları ve sağlık sektörü gibi alanlarda – hastalık teşhisi ve ilaç geliştirme dahil –hayati bir rol oynamaktadır. Son eğilimler, bilimsel araştırmalarda büyük dil modelleri ve doğal dil işleme kullanımının arttığını da göstermektedir. Çalışma, YZ'nin hem sosyal hem de doğa bilimleri araştırmalarında kilit bir unsur haline geldiği sonucuna varmaktadır. Sosyal bilim araştırmacılarına, psikoloji, hukuk ve eğitim üzerindeki YZ etkisinin daha fazla incelenmesi ve bibliyometrik yöntemlerin kullanılması önerilmektedir. Öte yandan, doğa bilimleri araştırmacılarına YZ şeffaflığını artırmaya, daha doğru teknolojiler geliştirmeye ve YZ'yi çevresel ve endüstriyel araştırmalarda uygulamaya odaklanmaları tavsiye edilmektedir. YZ gelişiminin etik ve kapsayıcı kalmasını sağlamak için disiplinler arası iş birliği gereklidir.

Keywords

Yapay Zekâ , Sosyal Bilimler , Doğa Bilimleri , Bibliyometrik İnceleme , Araştırma

Trends in Using Artificial Intelligence in Social and Natural Science Research

Abstract

This article discusses trends in the use of artificial intelligence (AI) in social sciences and natural sciences research. The introduction highlights how AI has evolved into an essential tool in both fields, addressing the limitations of traditional methods in social sciences and accelerating data analysis in natural sciences. The research method used is bibliometric analysis, with data collected from Google Scholar using keywords related to AI in social and natural sciences. Relevant articles were selected through a content evaluation and exclusion process, resulting in 1,000 social science publications and 999 natural science publications, which were further analyzed using VOSviewer with such as being outside the five-year range (published from 2020 to 2025). The study's findings indicate that in social sciences, AI is widely used to enhance research effectiveness through faster data processing, particularly in higher education and social policy analysis. Additionally, AI studies in social sciences are expanding, focusing on ethics, regulation, and human-AI interaction. In natural sciences, AI plays a crucial role in resource management, environmental research, and the healthcare industry, including disease diagnosis and drug development. Recent trends also show an increasing use of large language models (LLMs) and natural language processing (NLP) in scientific research. The study concludes that AI has become a key element in both social and natural science research. Recommendations for social science researchers include further exploration of AI’s impact on psychology, law, and education, as well as the use of bibliometric methods. Meanwhile, natural science researchers are advised to focus on improving AI transparency, developing more accurate technologies, and applying AI in environmental and industrial research. Interdisciplinary collaboration is necessary to ensure AI development remains ethical and inclusive.

Keywords

Artificial Intelligence , Social Science , Natural Science , Bibliometric Review , Research

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