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Journals / Muhasebe Bilim Dünyası Dergisi / 2026 / Cilt: 28 Sayı: 3

ARTIFICIAL INTELLIGENCE IN AUDITING AND ACCOUNTING: A BIBLIOMETRIC ANALYSIS

DENETİM VE MUHASEBEDE YAPAY ZEKÂ: BİBLİYOMETRİK BİR ANALİZ

Aysun Atagan Çetin(TRAKYA ÜNİVERSİTESİ)0000-0001-7588-1322
Pages
300–320
Publication Date
2026-09-27
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AI Summary & Key Takeaways

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

The findings indicate that bibliometric indicators vary depending on the data source, and that Scopus text networks offer a narrower, source-specific view of the core themes represented in the accessed records.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Artificial intelligence (AI) is addressed in accounting and auditing research in relation to financial reporting, assurance services, fraud detection, risk management, and professional decision-making processes.
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Key Findings & Data:Records, citations, annual citations, author-focused metrics, and the Age-Weighted Citation Rate accessed via Publish or Perish from Google Scholar, CrossRef, OpenAlex, Scopus, and Semantic Scholar data sources were compared.
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Conclusion & Impact:The findings indicate that bibliometric indicators vary depending on the data source, and that Scopus text networks offer a narrower, source-specific view of the core themes represented in the accessed records.
🔬Design:Araştırma Makalesi
📍Scope:Comprehensive Sample
⚙️Variables:Yapay Zekâ · Denetim · Muhasebe

Abstract

Artificial intelligence (AI) is addressed in accounting and auditing research in relation to financial reporting, assurance services, fraud detection, risk management, and professional decision-making processes. This study combines data source-sensitive bibliometric profiling with VOSviewer-based text network analysis. Records, citations, annual citations, author-focused metrics, and the Age-Weighted Citation Rate accessed via Publish or Perish from Google Scholar, CrossRef, OpenAlex, Scopus, and Semantic Scholar data sources were compared. The findings indicate that bibliometric indicators vary depending on the data source, and that Scopus text networks offer a narrower, source-specific view of the core themes represented in the accessed records.

Özet

Yapay zekâ (YZ), muhasebe ve denetim araştırmalarında finansal raporlama, güvence hizmetleri, hile tespiti, risk yönetimi ve mesleki karar alma süreçleriyle ilişkili olarak ele alınmaktadır. Bu çalışma, veri kaynağına duyarlı bibliyometrik profillemeyi VOSviewer temelli metin ağı analiziyle birleştirmektedir. Google Scholar, CrossRef, OpenAlex, Scopus ve Semantic Scholar veri kaynaklarından Publish or Perish aracılığıyla erişilen kayıt, atıf, yıllık atıf, yazar odaklı metrikler ve Yaşa Göre Ağırlıklandırılmış Atıf Oranı karşılaştırılmıştır. Bulgular, bibliyometrik göstergelerin veri kaynağına göre değiştiğini ve Scopus metin ağlarının erişilen kayıtlarda temsil edilen temel temalara ilişkin daha dar, kaynak-özel bir görünüm sunduğunu göstermektedir.

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Cite This Article

Çetin, A. A. (2026). ARTIFICIAL INTELLIGENCE IN AUDITING AND ACCOUNTING: A BIBLIOMETRIC ANALYSIS. Muhasebe Bilim Dünyası Dergisi, Cilt: 28 Sayı: 3, 300–320. https://doi.org/10.31460/mbdd.1591911

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