Academic Librarianship and Information Research

Academic Librarianship and Information Research

Divergence or Convergence Between the Language of Science and Public Demand in the Field of Artificial Intelligence and Information Seeking Behavior: A Comparative Analysis of Google Trends and Web of Science

Document Type : Research Article

Authors
MohammadReza Khoramabadi Arani
Yeganeh Dastar
Ali Mansouri
Morteza Mohammadi Ostani
Department of Knowledge & Information Science, Faculty of Education & Psychology, University of Isfahan, Isfahan, Iran.
10.22059/jlib.2026.419682.1837
Abstract
Objective: This study aims to compare general search patterns and scientific outputs in the field of artificial intelligence (AI) and information-seeking behavior by analyzing data from Google Trends and the Web of Science. Employing a mixed-methods approach, this research examines the degree of alignment or divergence among frequently occurring concepts, geographical distribution, and temporal trends in order to provide a realistic picture of the relationship between public information needs and research orientations.
Method: This applied research adopted a quantitative approach, utilizing scientometric and data-mining methods and integrating data from Google Trends and the Web of Science database. The research population comprised all documents indexed in the Web of Science in the relevant field. Analyses were conducted using VOSviewer, RStudio, and the PyTrends library in Python, focusing on three main axes: geographical overlap analysis, time-lag investigation, and comparison of frequently occurring terms and themes in public searches with keywords from scientific articles.
Results: Findings revealed that while countries such as China and the United States lead in scientific production in this domain, some developing nations—including Ethiopia and Nigeria—exhibit very low levels of public searches due to infrastructural limitations, suggesting that interpretations of divergence in such contexts should be approached with caution. At the lexical level, the specialized term “information-seeking behavior” was absent from public searches and was replaced by more tangible phrases such as “AI search.” Thematic clustering in this domain encompassed “human and cognitive dimensions,” “technology acceptance,” “technical infrastructure,” and “social implications.” Furthermore, a semantic gap between the language of science and public language was observed, along with a time lag between peaks in public interest and the publication of scientific articles. Scientific outputs were primarily focused on technical and algorithmic aspects, whereas public searches emphasized practical and interactive dimensions.
Conclusions: The results indicate a significant divergence across geographical, lexical, and conceptual dimensions between public demand and scientific outputs in the field of AI and information-seeking behavior. Recognizing this linguistic and temporal gap appears essential for aligning research orientations with actual societal needs, guiding research more effectively, and developing library and information services grounded in the authentic expectations of ordinary users
Keywords
artificial intelligence
information-seeking behavior
scientometrics
Google Trends
Web of Science
رسولی، بهروز، نعیمی صدیق، علی، جلالی‌منش، عمار و سمائی، سید مهدی (1404). کارکردهای هوش مصنوعی در کتابخانه‌های عمومی: مروری نظام‌مند. تحقیقات اطلاع‌رسانی و کتابخانه‌های عمومی، 31 (1)، 1–20. https://doi.org/10.61882/publlij.2025.2064863.1003
کاشانی، مصطفی، و داستانی، میثم (۱۴۰۳). تحلیل روند موضوعی تولیدات علمی پژوهشگران ایرانی درزمینة هوش مصنوعی در علوم پزشکی: مطالعه علم‌سنجی. اطلاع‌رسانی پزشکی نوین، ۱۰ (۳)، ۲۳۱–۲۴۶.
فرزین یزدی، محبوبه، و رضایی شریف‌آبادی، سعید (۱۳۹۶). بررسی تولیدات علمی حوزه موضوعی هوش مصنوعی در کشورهای خاورمیانه طی سال‌های ۱۹۹۶ تا ۲۰۱۴. پژوهش‌نامه علم‌سنجی، ۳ (۲(، ۹۷–۱۱۴. https://doi.org/10.22070/rsci.2017.512
هنرجویان، زهره، و میرزابیگی، مهدیه (۱۴۰۳). نقش تجربه، دانش موضوعی، و زبان کاربران در رفتار توقف جستجوی اطلاعات. تحقیقات کتابداری و اطلاع‌رسانی دانشگاهی، ۵۸) ۴)، 1–23. https://doi.org/10.22059/jlib.2025.390794.1773
عطاپور، هاشم، مجیدی، اکبر، و فرجی اردشیر، زهرا (۱۴۰۴). بررسی رفتار اطلاع‌یابی دانشجویان دانشگاه تبریز با تأکید ویژه بر ابزارهای هوش مصنوعی. تحقیقات کتابداری و اطلاع‌رسانی دانشگاهی، ۵۹ (۴)، ۱–۲۲. https://doi.org/10.22059/jlib.2026.407273.1805
Agrawal, K. (2025). The future of AI in digital search: Towards a fully conversational experience. Journal of Computer Science and Technology Studies, 7(4), 298–306. https://doi.org/10.32996/jcsts.2025.7.4.34
Atapour, H., Majidi, A., & Faraji Ardashir, Z. (2025). Studying the information seeking behavior of University of Tabriz students with special emphasis on artificial intelligence tools. Academic Librarianship and Information Research, 59(4), 1–22. https://doi.org/10.22059/jlib.2026.407273.1805 (in Persian)
Becher, T., & Trowler, P. R. (2001). Academic tribes and territories: Intellectual enquiry and the culture of disciplines (2nd ed). Society for Research into Higher Education & Open University Press.
Belkin, N. J. (1980). Anomalous states of knowledge as a basis for information retrieval. Canadian Journal of Information Science, 5, 133–143.
Chen, J., Duan, Y., Xia, H., et al. (2025). Online health information seeking behavior among breast cancer patients and survivors: A scoping review. BMC Women’s Health, 25(1). https://doi.org/10.1186/s12905-024-03509-x
Farzin Yazdi, M., & Rezaei Sharifabadi, S. (2017). Scientific publications in the subject area of artificial intelligence in Middle Eastern countries during 1996 to 2014. Scientometrics Research Journal, 3(2), 97–114. https://doi.org/10.22070/rsci.2017.512 (in Persian)
Honarjouyan, Z., & Mirzabeigi, M. (2024). The role of information search experience, domain knowledge, and user language on information search stopping behaviour. Academic Librarianship and Information Research, 58(4), 1–23. https://doi.org/10.22059/jlib.2025.390794.1773 (in Persian)
Kashani, M., & Dastani, M. (2024). Analysis of thematic trends in scientific publications of Iranian researchers in artificial intelligence for medical sciences: A scientometric study. Journal of Modern Medical Information Sciences, 10(3), 231–246. http://jmis.hums.ac.ir/article-1-543-fa.html (in Persian)
Kim, S. J., Clark, V., Hancock, J. T., Rawassizadeh, R., Liu, H., Taylor, E. A., & Sheppard, V. B. (2025). Leveraging artificial intelligence-mediated communication for cancer prevention and control and drug addiction: A systematic review. Translational Behavioral Medicine, 15 (1), ibaf.007. https://doi.org/10.1093/tbm/ibaf007
Militello, J. (2025). Mediating social and informational serendipity. Language & Communication, 100, 274–291. https://doi.org/10.1016/j.langcom.2024.12.010
Müller-Pérez, J., Acevedo-Duque, Á., García-Salirrosas, E. E., Escobar-Farfán, M., Esponda-Pérez, J. A., Cachicatari-Vargas, E., Álvarez-Becerra, R., & Alcina De Fortoul, S. (2025). Factors influencing healthy product consumer behavior: An integrated model of purchase intention. Frontiers in Public Health, 13, Article 1576427. https://doi.org/10.3389/fpubh.2025.1576427
Rasuli, B., Naimi-Sadigh, A., Jalalimanesh, A., & Samaei, S. M. (2025). Applications of artificial intelligence in public libraries: A systematic review. Research on Information Science and Public Libraries, 31 (1), 1–20. https://doi.org/10.61882/publlij.2025.2064863.1003 (in Persian)
Savolainen, R. (2005). Everyday life information seeking (pp. 143-148). [Publisher not identified].
Schneider, F. (2025). Exploring the notion of specialized language from diverse perspectives. Journal of Language Science and Practice, 1(1), 14–19. https://www.focuscholar.com/journal/index.php/jlsp/article/view/15
Schneider, P., Poelman, W., Rovatsos, M., & Matthes, F. (2024). Engineering conversational search systems: A review of applications, architectures, and functional components. arXiv preprint arXiv:2407.00997. https://aclanthology.org/2024.nlp4convai-1.5/
Shi, Y., Xu, H., Kwok, H. L., & Liu, K. (2025). ChatGPT in professional translation: A double-edged sword–Insights from Chinese translators on capabilities, concerns, and future prospects. In Translation studies in the age of artificial intelligence (pp. 125–149). Routledge. https://doi.org/10.4324/9781003482369-7
Tichenor, P. J., Donohue, G. A., & Olien, C. N. (1970). Mass media flow and differential growth in knowledge. Public Opinion Quarterly, 34 (2), 159–170. https://doi.org/10.1086/267786
Umkabu, S. R. I., & Rani, A. D. (2025). Information search patterns of information science students from TikTok and Twitter to theory with an Ellis lens. Journal of Information Science in Technology, 1 (2), 62–69. https://ejournal.upnvj.ac.id/jisty/article/view/11530
Wagner, G., Lukyanenko, R., & Paré, G. (2022). Artificial intelligence and the conduct of literature reviews. Journal of Information Technology, 37(2), 209–226. https://doi.org/10.1177/02683962211048201
Wilson, T. D. (1999). Models in information behaviour research. Journal of Documentation, 55(3), 249–270. https://doi.org/10.1108/EUM0000000007145
Zheng, C., Zhang, Y., Huang, Z., Shi, C., Xu, M., & Ma, X. (2024). DiscipLink: Unfolding interdisciplinary information seeking process via human-AI co-exploration. In Proceedings of the 37th Annual ACM Symposium on User Interface Software and Technology (pp. 1–20). https://doi.org/10.1145/3654777.3676366
Academic Librarianship and Information Research
Volume 60, Issue 2
Spring 2026
Pages 1-28