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cc-by-nc (c)  Vállez,  Mari et al., 2025
Si us plau utilitzeu sempre aquest identificador per citar o enllaçar aquest document: https://hdl.handle.net/2445/232240

Search engine visibility of university AI content: an analysis of thirty institutions from three countries

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Purpose: This study aims to investigate the search engine visibility of web content published by universities about artificial intelligence (AI), with the aim of evaluating their digital communication and dissemination strategies. The analysis focuses on the highest-ranking AI-related content found on Google, based on the domains of 30 universities from three countries. Web analysis tools are used to measure the visibility and impact of this content, enabling the identification of patterns and areas for improvement in the digital dissemination strategies of these academic institutions. Design/methodology/approach: To carry out this task, the first step was to determine the web visibility of the universities studied using SEMrush for the terms Artificial Intelligence/Generative Artificial Intelligence, OpenAI, ChatGPT/GPT. This quantitative analysis was complemented by a mixed-method approach, focusing on the analysis and evaluation of specific ranking factors present in the highest-ranking pages, with the aim of identifying best practices. Findings: The results confirm that while the universities analysed are active content creators, they do not achieve notable Web visibility when searching for information on AI or related keywords using search engines. Among the 30 universities studied, only three stand out in terms of the number of ranked webpages. Originality/value: While research on SEO has been conducted across various fields, no studies have yet explored the intersection of university Web visibility and searches for information on artificial intelligence in search engines. The key contributions that set this study apart are, firstly, its global perspective on the web visibility of AI-related content produced by universities and, secondly, its value-added recommendations for enhancing their online presence.

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VÁLLEZ, Mari, ALCARAZ MARTÍNEZ, Rubén and LOPEZOSA, Carlos. Search engine visibility of university AI content: an analysis of thirty institutions from three countries. Digital Library Perspectives. 2025. Vol. 1-19. ISSN 2059-5816. [consulted: 24 of October of 2026]. Available at: https://hdl.handle.net/2445/232240

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