Detecting AI adoption at scale: a web mining and LLM methodology

Abstract The recent emergence of Artificial Intelligence (AI) technologies has created multiple opportunities for companies. The growing interest in AI adoption has led to an increase in technological innovations and business applications. At the same time, web mining techniques have been used to monitor technological trends, often through basic natural language processing methods. However, advances in Large Language Models (LLMs) enable a more detailed and in-depth analysis of web content, necessitating the development of new methodologies. This paper proposes a methodology for integrating LLMs into the technology mining of corporate websites, with a focus on Spanish companies. The study uses data collected in 2023 and 2025, applying web scraping techniques to gather textual information. The analysis process involves automated AI detection, manual validation, and evaluation through standard classification metrics. The findings contribute to a better understanding of AI adoption trends and inform future research on tech mining applications for industry.

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Publication Details

Journal
Scientometrics
Published
2025-11-25
DOI
https://doi.org/10.1007/s11192-025-05468-y
Citations
2
Primary Topic
Web Data Mining and Analysis
Type
article
Field-Weighted Citation Impact
6.49

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article

Detecting AI adoption at scale: a web mining and LLM methodology

Josep Domènech, Ana Pastor-Merino, Xavier Martínez-Barbero
2 citations
Scientometrics
Web Data Mining and Analysis
6.49
article

Detecting AI adoption at scale: a web mining and LLM methodology

Josep Domènech, Ana Pastor-Merino, Xavier Martínez-Barbero
article en
2 citations

Abstract

Abstract The recent emergence of Artificial Intelligence (AI) technologies has created multiple opportunities for companies. The growing interest in AI adoption has led to an increase in technological innovations and business applications. At the same time, web mining techniques have been used to monitor technological trends, often through basic natural language processing methods. However, advances in Large Language Models (LLMs) enable a more detailed and in-depth analysis of web content, necessitating the development of new methodologies. This paper proposes a methodology for integrating LLMs into the technology mining of corporate websites, with a focus on Spanish companies. The study uses data collected in 2023 and 2025, applying web scraping techniques to gather textual information. The analysis process involves automated AI detection, manual validation, and evaluation through standard classification metrics. The findings contribute to a better understanding of AI adoption trends and inform future research on tech mining applications for industry.

Scientometrics
Universitat Politècnica de València (ES)
Generalitat Valenciana, Universitat Politècnica de València, European Regional Development Fund, Agencia Estatal de Investigación
Openalex Percentile: Top 3%
Web Data Mining and Analysis
6.49
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Detecting AI adoption at scale: a web mining and LLM methodology — Josep Domènech, Ana Pastor-Merino, et al. · Scientometrics (2025) | TGRS Research Map | TGRS