YBB'ler ile Teknoloji Madenciliği: Kurumsal Web Sitelerinden Trendleri Ortaya Çıkarmak

Özet (abstract)

Abstract Technology mining enables the systematic extraction and analysis of trends regarding scientific and technological developments from diverse Science, Technology, and Innovation (ST&I) data sources. Traditionally, indicators such as patents, surveys, and R&D statistics have been widely used to monitor technological change and innovation. This study proposes a novel methodology leveraging semantic analysis of corporate website content using large language models (LLMs) to facilitate real-time monitoring of technological developments. Specifically, we focus on Spanish manufacturing firms that have adopted artificial intelligence (AI). A pipeline was developed to automatically extract and classify bigrams and unigrams from corporate websites into technological and non-technological terms, enabling a temporal analysis of technologies for the years 2023 and 2025. The results indicate an increase in AI-related mentions, as well as notable patterns of co-occurrence with Internet of Things (IoT) and Industry 4.0 technologies. Our study demonstrates the utility of the combination of corporate websites and LLMs as scalable, dynamic, and cost-effective sources for technology mining, contributing methodologically through advanced text analytics and empirically by providing granular, web-derived insights into technological dynamics within the manufacturing sector.

Yazarların özeti; kaynağından alınmıştır. Computational Economics, 2026 · DOI ↗