Journals / Uluslararası Batı Karadeniz Sosyal ve Beşeri Bilimler Dergisi / 2026 / Cilt: 10 Sayı: 1

ASSESSING THE PRESENCE OF AI IN ARTICLES: EVIDENCE FROM PUBLISHED STUDIES

MAKALELERDE YAPAY ZEKÂ VARLIĞININ DEĞERLENDİRİLMESİ: YAYINLANMIŞ ÇALIŞMALARDAN ELDE EDİLEN BULGULAR

Ahmet Akkaya(Bartın Üniversitesi, Eğitim Fakültesi, Türkçe ve Sosyal Bilimler Eğitimi Bölümü)0000-0003-3845-8992
Burak Beygirci(BARTIN ÜNİVERSİTESİ)0000-0002-0666-4436
Pages
1–31
Publication Date
2026-03-23
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The findings indicate that AI-detection outputs vary meaningfully by indexing status and disciplinary field.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:The growing use of generative artificial intelligence (GenAI) tools in academic writing has increased concerns about the visibility of AI traces in scientific publications and the potential implications for publication ethics.
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Key Findings & Data:This study compares the presence of AI-generated text in Turkish open-access research articles published in 2025, focusing on the disciplinary field and indexing status.
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Conclusion & Impact:The findings indicate that AI-detection outputs vary meaningfully by indexing status and disciplinary field.
🔬Design:Review & Systematic Survey
📍Scope:2025 Verileri
⚙️Variables:Üretken yapay zekâ · Yapay zekâ metin tespiti · Akademik yazım

Abstract

The growing use of generative artificial intelligence (GenAI) tools in academic writing has increased concerns about the visibility of AI traces in scientific publications and the potential implications for publication ethics. In parallel, journals and policy actors have begun to more explicitly define authors' responsibilities and acceptable ways to acknowledge and cite GenAI use. This study compares the presence of AI-generated text in Turkish open-access research articles published in 2025, focusing on the disciplinary field and indexing status. The dataset comprises 204 articles drawn from 68 university-published journals hosted on DergiPark. All articles were screened using the Assistin.ai AI-text detection tool. Journals indexed in TR Dizin and those not indexed, as well as science-oriented and social science–oriented fields, were compared using a balanced design. The findings indicate that AI-detection outputs vary meaningfully by indexing status and disciplinary field. Probabilistic AI-text signals were higher in social science–oriented journals than in science-oriented journals, and higher in non–TR Dizin journals than in TR Dizin–indexed journals. Section-level analyses further show that AI signals were most frequently observed in the Introduction/Literature Review and Interpretation/Discussion of Findings sections. At the same time, they were comparatively lower in the Methods and Conclusion sections. In addition, the reference lists of all articles were manually verified. The analysis identified at least one hallucinated (fabricated) reference in 37 articles, and the likelihood of hallucinated references increased as the detected AI ratio rose. By providing a multi-layered assessment of GenAI visibility in Turkish articles across indexing status, disciplinary field, and manuscript sections, this study offers evidence-based implications for journal and university publishing policies, ethical use, transparency practices, and author accountability.

Özet

Üretken yapay zekâ araçlarının akademik yazım süreçlerinde araştırmacılar tarafından kullanımının artmasıyla üretilen bilimsel yayınlarda yapay zekâ izinin ortaya çıktığı ve yayın etiği bağlamında oluşturacağı sonuçlar tartışılır hale gelmiştir. Ayrıca yapay zekâ kullanımında yazar sorumlulukları ve ÜYZ araçlarına atıf verme biçimleri politika yapıcılar ve dergiler tanımlanır olmuştur. Bu çalışma, 2025 yılında yayımlanmış ve ücretsiz olarak erişilebilen Türkçe akademik makalelerdeki yapay zekâ varlığını konu alanı ve indeksleme durumuna göre karşılaştırmalı olarak incelemektedir. Çalışma, DergiPark’ta yayımlanmış ve üniversite yayını olan 68 dergiden seçilen toplamda 204 makale üzerinden yürütülmüştür. Makaleler, assistin.ai yapay zekâ tespit aracıyla taranmıştır. TR Dizin’de indekslenen ve indekslenmeyen dergiler ile fen temelli ve sosyal konu alanına sahip dergiler eşit dağılımla karşılaştırılmıştır. Elde edilen bulgular, metinlerde yapay zekâ kullanımının dergilerin indekslenme ve konu alanı durumuna göre anlamlı ve belirgin farklılıklar gösterdiğini ortaya koymuştur. Olasılıksal olarak YZ kullanım durumu, sosyal temelli konu alanına sahip dergilerde fen temelli dergilere göre daha yüksek düzeyde tespit edilmiş; TRDizin’de indekslenmeyen dergilerde de TRDizinli dergilere göre daha yüksek oranlara sahip olduğu belirlenmiştir. Makalelerin bölüm bazlı analizleri de gerçekleştirilmiş olup en yüksek oranların “giriş/literatür” ve “bulguların yorumlanması” bölümlerinde ortaya çıktığı; “yöntem” ve “sonuç” bölümlerinde diğer bölümlere kıyasla görece daha düşük düzeyde olduğu ortaya konulmuştur. Ayrıca tüm makalelere yönelik olarak kaynakça analizi gerçekleştirilmiştir. Manuel olarak tek tek kaynak tarama şeklinde yürütülen çalışmada, toplamda 37 makalede en az 1 kez halisünasyon (uydurma) kaynak kullanıldığı tespit edilmiştir. Genel olarak makalelerdeki YZ kullanım oranlarına göre ilişkisel düzeye bakıldığında ise oran yükseldikçe kaynakçalarda halisünasyon yayınların varlığının arttığı gözlenmiştir. Çalışma, Türkiye’de üretilmiş olan makalelerdeki üretken yapay zekâ kullanımı varlığını indeks, konu alanı ve metin alt bölümü düzeyinde çok katmanlı olarak analiz eden ilk araştırmalardan biri olarak, dergi ve üniversite yayın politikaları, etik kullanım, şeffaflık ve yazar sorumluluklarına yönelik önemli çıkarımlar sunmaktadır.

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Cite This Article

Akkaya, A., Beygirci, B. (2026). ASSESSING THE PRESENCE OF AI IN ARTICLES: EVIDENCE FROM PUBLISHED STUDIES. Uluslararası Batı Karadeniz Sosyal ve Beşeri Bilimler Dergisi, Cilt: 10 Sayı: 1, 1–31. https://doi.org/10.46452/baksoder.1899625

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