نوع مقاله : مقاله پژوهشی
عنوان مقاله English
نویسندگان English
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
کلیدواژهها English
