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Journals / Black Sea Journal of Engineering and Science / 2026 / Cilt: 9 Sayı: 2

AI-Powered Human-Computer Interaction: A Bibliometric Study

Murat Ertan Doğan(Yaşar Üniversitesi)0000-0001-6668-5952
Pages
854–863
Publication Date
2026-03-15
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AI Summary & Key Takeaways

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

This research provides a deeper understanding of the evolving landscape of AI and HCI and serves as a foundation for future studies.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:This study presents a thorough analysis of the Artificial Intelligence (AI) and Human-Computer Interaction (HCI) intersection, with the aim of identifying important trends, themes, and influential research in this rapidly changing field.
📊
Key Findings & Data:The integration of AI into HCI has resulted in significant advancements across various domains, such as healthcare, education, and user experience design.
💡
Conclusion & Impact:This research provides a deeper understanding of the evolving landscape of AI and HCI and serves as a foundation for future studies.
🔬Design:Review & Systematic Survey
📍Scope:2025 Verileri
⚙️Variables:Artificial intelligence · Human-computer Interaction · Explainable artificial intelligence

Abstract

This study presents a thorough analysis of the Artificial Intelligence (AI) and Human-Computer Interaction (HCI) intersection, with the aim of identifying important trends, themes, and influential research in this rapidly changing field. The integration of AI into HCI has resulted in significant advancements across various domains, such as healthcare, education, and user experience design. Although there is a growing interest in this area, the number of studies is still limited, and the research is gradually increasing. This study aims to fill the gap by providing a comprehensive overview of the current literature, focusing on the gaps, emerging trends, and future directions in AI-driven HCI. The research methodology adheres to the PRISMA protocol, which guarantees a systematic and clear review process. A total of 84 peer-reviewed publications from the Scopus database, spanning a 30-year period from 1994 to 2025, were examined. The research corpus was subjected to bibliometric analysis, Social Network Analysis (SNA), and text mining techniques to map the landscape of AI and HCI research. The study also recognized key authors, influential countries, and significant academic sources contributing to this field. The results of the analysis identified five primary thematic groups: Explainable AI (XAI), Human-Computer Interaction (HCI) and AI in Education and Training, Human-Robot Interaction (HRI), and AI and User Experience (UX). These themes emphasize the wide-ranging applications of AI in HCI, such as enhancing diagnostic precision in healthcare, personalizing educational content, and enhancing user experience through adaptive and emotionally intelligent interfaces. However, the study also revealed significant gaps in the existing literature, particularly regarding ethical considerations, transparency, and user control. The analysis indicates that ethical issues are not adequately emphasized in current research, suggesting a crucial area for future investigation. The study suggests that while AI has considerable potential to transform HCI, its successful incorporation will depend on addressing these gaps and ensuring that AI-driven systems prioritize human-centered design principles. The results also highlight the prominent role of countries like the People's Republic of China (PRC) in advancing this field, and emphasize the need for broader international cooperation. This research provides a deeper understanding of the evolving landscape of AI and HCI and serves as a foundation for future studies.

Özet

This study presents a thorough analysis of the Artificial Intelligence (AI) and Human-Computer Interaction (HCI) intersection, with the aim of identifying important trends, themes, and influential research in this rapidly changing field. The integration of AI into HCI has resulted in significant advancements across various domains, such as healthcare, education, and user experience design. Although there is a growing interest in this area, the number of studies is still limited, and the research is gradually increasing. This study aims to fill the gap by providing a comprehensive overview of the current literature, focusing on the gaps, emerging trends, and future directions in AI-driven HCI. The research methodology adheres to the PRISMA protocol, which guarantees a systematic and clear review process. A total of 84 peer-reviewed publications from the Scopus database, spanning a 30-year period from 1994 to 2025, were examined. The research corpus was subjected to bibliometric analysis, Social Network Analysis (SNA), and text mining techniques to map the landscape of AI and HCI research. The study also recognized key authors, influential countries, and significant academic sources contributing to this field. The results of the analysis identified five primary thematic groups: Explainable AI (XAI), Human-Computer Interaction (HCI) and AI in Education and Training, Human-Robot Interaction (HRI), and AI and User Experience (UX). These themes emphasize the wide-ranging applications of AI in HCI, such as enhancing diagnostic precision in healthcare, personalizing educational content, and enhancing user experience through adaptive and emotionally intelligent interfaces. However, the study also revealed significant gaps in the existing literature, particularly regarding ethical considerations, transparency, and user control. The analysis indicates that ethical issues are not adequately emphasized in current research, suggesting a crucial area for future investigation. The study suggests that while AI has considerable potential to transform HCI, its successful incorporation will depend on addressing these gaps and ensuring that AI-driven systems prioritize human-centered design principles. The results also highlight the prominent role of countries like the People's Republic of China (PRC) in advancing this field, and emphasize the need for broader international cooperation. This research provides a deeper understanding of the evolving landscape of AI and HCI and serves as a foundation for future studies.

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Cite This Article

Doğan, M. E. (2026). AI-Powered Human-Computer Interaction: A Bibliometric Study. Black Sea Journal of Engineering and Science, Cilt: 9 Sayı: 2, 854–863. https://doi.org/10.34248/bsengineering.1868191

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