EVALUATING LOCAL SEO QUALITY OF MUNICIPAL GEOPORTALS: A MULTI-METHOD APPROACH INTEGRATING AUTOMATED, LINK, AND AI-BASED ANALYSIS
EVALUATING LOCAL SEO QUALITY OF MUNICIPAL GEOPORTALS: A MULTI-METHOD APPROACH INTEGRATING AUTOMATED, LINK, AND AI-BASED ANALYSIS
Author(s): Karol KrólSubject(s): Applied Geography, Public Administration, ICT Information and Communications Technologies
Published by: Wydawnictwo Uniwersytetu Warmińsko-Mazurskiego w Olsztynie
Keywords: Large Language Models; passive SEO; mechanical SEO audit; Local SEO; theoretical SEO audit; geoinformation;
Summary/Abstract: Motives: Research on search engine optimisation (SEO) usually focuses on commercial websites, with limited attention to public sector platforms like geoportals. The impact of SEO on their online visibility and Local SEO quality remains understudied, which presents a research gap worth exploring. Aim: This study evaluates the SEO quality of selected municipal geoportals using Large Language Models (LLMs). It examines how well these portals are optimised for search engines and whether AI tools can effectively support SEO auditing. Results: Audits of five geoportals using tools like ChatGPT, Copilot, Gemini, and Perplexity revealed low SEO support from public administrations, poor link building, and weak metadata. Referring domains and quality indicators were limited. Moreover, AI tools do not conduct real-time audits, which restricts their accuracy and usefulness for detailed SEO assessments.
Journal: Acta Scientiarum Polonorum Administratio Locorum
- Issue Year: 24/2025
- Issue No: 4
- Page Range: 605-622
- Page Count: 18
- Language: English
