İNSAN-BİLGİSAYAR ETKİLEŞİMİ ALANINDAKİ ARAŞTIRMA EĞİLİMLERİNİN LEXİMANCER İLE TEMATİK ANALİZİ

Öz

Bilgisayar teknolojilerinin hızlı gelişimi, insan yaşamının hemen her alanında bilgisayarlarla etkileşimi vazgeçilmez hale getirmiştir. Bu durum, insan-bilgisayar etkileşimi (İBE) araştırmalarının önemini artırmış ve bu alanda farklı yaklaşım ve temaların incelenmesini gerekli kılmıştır. Bu araştırma, International Journal of Human–Computer Interaction dergisinde 1994–2025 yılları arasında yayımlanan makaleleri tematik açıdan analiz ederek HCI alanındaki gelişim ve eğilimleri ortaya koymayı amaçlamaktadır. Bu çalışma kapsamında dijital etkileşim süreci kronolojik ve tematik açıdan dört temel döneme ayrılmıştır: 1994-2002 yılları arası Erken Dönem Dijital Etkileşim, 2003-2011 yılları arası Web ve Mobil Genişleme Dönemi, 2012-2019 yılları arası Akıllı Sistemler ve Deneyim Odaklı Etkileşim Dönemi ve 2020-2025 yıllarını kapsayan süreç ise Yapay Zekâ ile Etik/Hibrit Etkileşim Dönemi olarak sınıflandırılmıştır. Çalışmada, metin madenciliği yaklaşımı kapsamında Leximancer analiz aracı kullanılmış ve toplam 3.776 makalenin özetleri incelenerek kavramsal haritalar oluşturulmuştur. Bulgular, HCI alanında ‘tasarım’, ‘çalışma’, ‘kullanıcı’ ve ‘sistem’ gibi temel kavramların süreklilik gösterdiğini ortaya koymaktadır. 1994-2002 yıllarını kapsayan Erken dönemde ‘arayüz’, ‘görev’, ‘performans’ ve ‘kullanılabilirlik’ gibi teknik ve uygulama odaklı kavramlar ön planda iken; 2012-2025 yılları arasındaki dönemlerde ‘deneyim’, ‘etkileşim’, ‘teknoloji’, ‘sosyal’ ve ‘öğrenme’ gibi kullanıcı merkezli ve bağlamsal temalar öne çıkmıştır.

Anahtar Kelimeler

• İnsan-Bilgisayar Etkileşimi
• Metin Madenciliği
• Leximancer.

THEMATIC ANALYSIS OF RESEARCH TRENDS IN HUMAN–COMPUTER INTERACTION USING LEXIMANCER

Öz

The rapid advancement of computer technologies has rendered interaction with computers indispensable across nearly every facet of human life. This phenomenon has elevated the significance of Human-Computer Interaction (HCI) research, necessitating an investigation into diverse approaches and themes within the field. This study aims to reveal the evolution and trends in HCI by conducting a thematic analysis of articles published in the International Journal of Human–Computer Interaction between 1994 and 2025. Within the scope of this research, the digital interaction process is categorized into four fundamental periods based on chronological and thematic criteria: the Early Digital Interaction Era (1994-2002), the Web and Mobile Expansion Era (2003-2011), the Smart Systems and Experience-Oriented Interaction Era (2012-2019), and the Artificial Intelligence and Ethical/Hybrid Interaction Era (2020-2025). Utilizing a text-mining approach, the Leximancer analysis tool was employed to examine the abstracts of 3,776 articles, resulting in the generation of conceptual maps. The findings indicate a continuity of core concepts in the HCI field, such as 'design', 'study', 'user', and 'system'. While technical and application-oriented concepts including 'interface', 'task', 'performance', and 'usability' were predominant during the early period (1994-2002), user-centered and contextual themes such as 'experience', 'interaction', 'technology', 'social', and 'learning' have become prominent in the periods spanning 2012-2025.

Anahtar Kelimeler

• Human–Computer Interaction
• Text Mining
• Leximancer.

Kaynakça

1. Alemdag, E., & Çağıltay, K. (2018). A systematic review of eye tracking research on multimedia learning. Computers & Education, 125, 413-428. https://doi.org/10.1016/j.compedu.2018.06.023
2. Angus, D., Rintel, S., & Wiles, J. (2013). Making sense of big text: A visual-first approach for analysing text data using Leximancer and Discursis. International Journal of Social Research Methodology, 16(3), 261-267. https://doi.org/10.1080/13645579.2013.774186
3. Azofeifa, J. D., Noguez, J., Ruiz, S., Molina-Espinosa, J. M., Magana, A. J., & Benes, B. (2022). Systematic review of multimodal human–computer interaction. Informatics, 9(1), 13, 1-32. https://doi.org/10.3390/informatics9010013
4. Bala, M. Y., & Damla, K. (2021). A review of human-computer interaction design approaches towards information systems development. BRAIN: Broad Research in Artificial Intelligence and Neuroscience, 12(1), 229-250. https://doi.org/10.18662/brain/12.1/180
5. Barutcu, E. I., & Gülseçen, S. (2024). Öğretim tasarımı araştırmalarında göz takibi teknolojisinin kullanılmasının bibliyometrik analizi. Journal of Research in Education and Teaching, 13(4), 29-38.
6. Capdevila, M. G., Saltiveri, T. G., Garrido, J. E., Müller, O. H., & Ruas, L. C. (2021). Do current user testing practices meet the needs of the new interactive paradigms? In Proceedings of the XXI International Conference on HCI (pp. 1-9). ACM. https://doi.org/10.1145/3471391.3471416
7. Carroll, J. M. (1997). Human–computer interaction: Psychology as a science of design. *International Journal of Human-Computer Studies, 46*(4), 501-522.
8. Carroll, J. M., & Campbell, R. L. (1989). Artifacts as psychological theories: The case of human-computer interaction. Behaviour & Information Technology, 8(4), 247-256.

9. Carvalho, R. M., de Castro Andrade, R. M., de Oliveira, K. M., de Sousa Santos, I., & Bezerra, C. I. M. (2017). Quality characteristics and measures for human–computer interaction evaluation in ubiquitous systems. Software Quality Journal, 25(3), 743-795. https://doi.org/10.1007/s11219-016-9320-z
10. Chandran, R. (2022). Human-computer interaction in robotics: A bibliometric evaluation using web of science. Metaverse Basic and Applied Research, 1(22), 1-9. https://doi.org/10.56294/mr202222
11. Gurcan, F., & Sevik, S. (2019). Human-computer interaction: A literature analysis from 1998 to 2018 using automated text mining. In 2019 1st International Informatics and Software Engineering Conference (UBMYK) (pp. 1-5). IEEE. https://doi.org/10.1109/UBMYK48245.2019.8965599
12. Gurcan, F., Çağıltay, N. E., & Çağıltay, K. (2021). Mapping human–computer interaction research themes and trends from its existence to today: A topic modeling-based review of past 60 years. International Journal of Human–Computer Interaction, 37(3), 267-280. https://doi.org/10.1080/10447318.2020.1819668
13. Hartson, H. R. (1998). Human–computer interaction: Interdisciplinary roots and trends. Journal of Systems and Software, 43(2), 103-118. https://doi.org/10.1016/S0164-1212(98)10026-2
14. Himmelsbach, J., Schwarz, S., Gerdenitsch, C., Wais-Zechmann, B., Bobeth, J., & Tscheligi, M. (2019). Do we care about diversity in human computer interaction: A comprehensive content analysis on diversity dimensions in research. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (pp. 1-16). https://doi.org/10.1145/3290605.3300720
15. Hinze-Hoare, V. (2007). The review and analysis of human computer interaction (HCI) principles. arXiv preprint arXiv:0707.3638. https://doi.org/10.48550/arXiv.0707.3638
16. Ho, M. R., Smyth, T. N., Kam, M., & Dearden, A. (2009). Human-computer interaction for development: The past, present, and future. Information Technologies & International Development, 5(4), 1-18.
17. Jiang, Q., & Huang, Y. (2023). Affective computing research progress and its implications for education technology: A bibliometric analysis based on web of science via VOSviewer. In 2023 4th International Conference on Artificial Intelligence and Education (ICAIE) (pp. 425-437). Atlantis Press. https://doi.org/10.2991/978-94-6463-242-2_53
18. Khan, A., Hussain, A., & Zareef, M. (2025). The use of human-computer interaction in libraries: A systematic literature review. Global Knowledge, Memory and Communication, 74(3/4), 864-882. https://doi.org/10.1108/GKMC-07-2022-0167
19. Li, R., Zhang, H., Liu, C., Qian, Z. C., & Zhang, L. (2022). Bibliometric and visualized analysis of user experience design research: From 1999 to 2019. SAGE Open, 12(1). https://doi.org/10.1177/21582440221087266
20. Liberati, A., Altman, D. G., Tetzlaff, J., Mulrow, C., Gøtzsche, P. C., Ioannidis, J. P., Clarke, M., Devereaux, P. J., Kleijnen, J., & Moher, D. (2009). The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: Explanation and elaboration. BMJ, 339. https://doi.org/10.1136/bmj.b2700
21. MacKenzie, I. S. (2024). Human-computer interaction: An empirical research perspective (2nd ed.). Morgan Kaufmann.
22. Man, Y., Lundh, M., & MacKinnon, S. N. (2018). Towards a pluralistic epistemology: Understanding human-technology interactions in shipping from psychological, sociological, and ecological perspectives. TransNav: International Journal on Marine Navigation and Safety of Sea Transportation, 12(4), 795-811. https://doi.org/10.12716/1001.12.04.20
23. Mehdipour, M., Chitsaz, E., & Etemadi, M. (2024). A perspective on human interaction and artificial intelligence: Bibliometric analysis with co-occurrence technique. Karafan Journal, 21(3), 13-33. https://doi.org/10.48301/KSSA.2024.428257.2778
24. Novák, J. Š., Masner, J., Benda, P., Šimek, P., & Merunka, V. (2024). Eye tracking, usability, and user experience: A systematic review. International Journal of Human–Computer Interaction, 40(17), 4484-4500. https://doi.org/10.1080/10447318.2023.2221600
25. Sanchez, C., Wang, S., Savolainen, K., Epp, F. A., & Salovaara, A. (2025). Let's talk futures: A literature review of HCI's future orientation. In Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems (pp. 1-36). ACM. https://doi.org/10.1145/3706598.3713759
26. Shiau, W. L., Yan, C. M., & Kuo, C. C. (2016). The intellectual structure of human computer interaction research. Journal of Information Science & Engineering, 32(3), 703-730.
27. Singh, V., Varalakshmi, S., Velusudha, N. T., Nawadkar, A. R., Srivastava, M., & Kalra, H. (2024). Text mining for automated data analysis and information retrieval. In 2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT) (pp. 1-6). IEEE. https://doi.org/10.1109/ICCCNT61001.2024.10725726
28. Sinha, G., Shahi, R., & Shankar, M. (2010). Human-computer interaction. In Proceedings of the 3rd International Conference on Emerging Trends in Engineering and Technology (pp. 1-4). IEEE. https://doi.org/10.1109/ICETET.2010.85
29. Solis-Pino, A. F., Ruiz, P. H., Agredo-Delgado, V., Mon, A., & Alberto Collazos, C. (2024). Bibliometric analysis of the research landscape in human-computer interaction in Ibero-America. Revista Tecno Lógicas, 27(59). https://doi.org/10.22430/22565337.2907
30. Sun, Q., & Duan, S. (2025). User intent prediction and response in human-computer interaction via BILSTM. Journal of Computer Science and Software Applications, 5(3). https://doi.org/10.5281/zenodo.14985042
31. Şimşek, A. I., Taşdemir, B. D., & Koç, E. (2023). Bibliometric analysis and research agenda of the location of electric vehicle charging stations. Business & Management Studies: An International Journal, 11(2), 610-625. https://doi.org/10.15295/bmij.v11i2.2246
32. Wang, J., Cheng, R., Liu, M., & Liao, P. C. (2021). Research trends of human–computer interaction studies in construction hazard recognition: A bibliometric review. Sensors, 21(18), 6172. https://doi.org/10.3390/s21186172
33. Ward, V., West, R., Smith, S., McDermott, S., Keen, J., Pawson, R., & House, A. (2014). The role of informal networks in creating knowledge among health-care managers: A prospective case study. Health Services and Delivery Research, 2(12). https://doi.org/10.3310/hsdr02120
34. Zhang, P., & Li, N. (2004). An assessment of human–computer interaction research in management information systems: Topics and methods. Computers in Human Behavior, 20(2), 125-147. https://doi.org/10.1016/j.chb.2003.10.011
35. Zhao, X., Zhang, S., Nan, D., Han, J., & Kim, J. H. (2024). Human–computer interaction in healthcare: A bibliometric analysis with Citespace. Healthcare, 12(23), 2467. https://doi.org/10.3390/healthcare12232467