Generative AI Performance Benchmarking: The Impact of ChatGPT and DeepSeek on User Interactions

Year 2025, Volume: 7 Issue: 1, 1 - 39, 30.06.2025

Koray Demirok , Fatih Eren , Yusuf Samet Akkaya , Dilek Çayirli

https://doi.org/10.53694/bited.1710862

Abstract

This study aims to evaluate and compare the performance and impact of generative AI models
ChatGPT and DeepSeek on user interactions through a comparative analysis. The research utilizes
a synthetic dataset obtained from Kaggle.com, encompassing over 10,000 user interaction records
collected between July 2023 and February 2025. Variables such as response accuracy, session
duration, and user satisfaction were analyzed using machine learning algorithms (regression,
decision trees, clustering) and statistical tests (t-test, ANOVA). The findings indicate that DeepSeek
received higher user ratings particularly in technical tasks (e.g., debugging, code optimization),
while ChatGPT stood out in areas such as content generation and education. DeepSeek users
generally reported higher experience scores and ratings, along with lower abandonment rates. The
study highlights the strengths, limitations, and user interaction dynamics of both platforms,
emphasizing that performance varies depending on the context of use and underlining the
importance of data privacy and ethical considerations.

Keywords

Generative Artificial Intelligence, ChatGPT, DeepSeek, User Interaction, Performance Comparison

Ethical Statement

The Ethical Committee Approval: This research does not require an ethics committee decision, since data in an international database open to all researchers are used.

Üretken Yapay Zeka Performans Kıyaslaması: ChatGPT ve DeepSeek'in Kullanıcı Etkileşimleri Üzerindeki Etkisi

Abstract

Bu çalışma, üretken yapay zekâ modelleri olan ChatGPT ve DeepSeek'in kullanıcı etkileşimleri
üzerindeki performansını ve etkisini karşılaştırmalı bir analizle değerlendirmeyi amaçlamaktadır.
Araştırmada, Kaggle.com'dan temin edilen ve Temmuz 2023 ile Şubat 2025 arasını kapsayan,
10.000'den fazla kullanıcı etkileşim verisi içeren sentetik bir veri seti kullanılmıştır. Makine
öğrenmesi algoritmaları (regresyon, karar ağaçları, kümeleme) ve istatistiksel testler (t-test,
ANOVA) aracılığıyla yanıt doğruluğu, oturum süresi, kullanıcı memnuniyeti gibi değişkenler
analiz edilmiştir. Bulgular, DeepSeek'in özellikle teknik görevlerde (hata ayıklama, kod
optimizasyonu) daha yüksek kullanıcı derecelendirmeleri aldığını, ChatGPT'nin ise içerik üretimi
ve eğitim gibi alanlarda öne çıktığını göstermiştir. DeepSeek kullanıcıları genel olarak daha
yüksek deneyim puanları ve derecelendirmeler bildirirken, daha düşük terk etme oranlarına sahip
olduğu gözlemlenmiştir. Çalışma, her iki platformun güçlü yönlerini, sınırlılıklarını ve kullanıcı
etkileşim dinamiklerini ortaya koyarak, platformların kullanım bağlamına göre performans
farklılıkları sergilediğini ve veri gizliliği ile etik konuların önemli olduğunu vurgulamaktadır.

Keywords

Üretken Yapay Zekâ, ChatGPT, DeepSeek, Kullanıcı Etkileşimi, Performans Kıyaslaması

Ethical Statement

Etik kurul kararı: Bu araştırmada, tüm araştırmacılara açık, uluslararası veri tabanında yer alan veriler kullanıldığından etik kurul kararı gerektirmemektedir.

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