欧洲边缘地区在人工智能研究上表现突出，但影响力与专业化不匹配。
Artificial Intelligence Specialization in the European Union: Underexplored Role of the Periphery at NUTS-3 Level
- 按区域层级分析781个欧盟小区域的AI研究分布。
- 东部欧洲和西班牙部分边缘区专业度最高，但引用影响力参差不齐。
- 高引用地区如丹麦菲英岛，虽专业度低却影响大，适合政策参考。
本研究分析2015-2024年间欧盟NUTS-3级区域的人工智能（AI）研究分布。基于Clarivate InCites的书目数据与引文主题分类系统，分析两个层级的主题：电气工程、电子与计算机科学（宏观引文主题4），以及人工智能与机器学习（中观引文主题4.61）。对781个欧盟区域计算相对专业化指数（RSI）与相对引用影响（RCI）。尽管巴黎、华沙、马德里等核心城市在论文数量上占优，但最高相对专业化集中于外围地区，尤以东欧和西班牙为甚。格拉纳达和维尔纽斯县表现尤为突出，兼具高专业化与强引用可见性。分析显示，区域专业化与引用影响力关联较弱，呈现多种模式：高度专业化但引用有限、高可见性但专业化较低，以及中等专业化与强引用并存的多样化科研体系。丹麦菲英地区为极端案例——引用影响极高，但专业化程度相对较低。
原文摘要 · Abstract (English)
This study examines the distribution of Artificial Intelligence (AI) research across European NUTS-3 regions during the period 2015-2024. Using bibliometric data from Clarivate InCites and the Citation Topics classification system, we analyse two hierarchical thematic levels: Electrical Engineering, Electronics & Computer Science (Macro Citation Topic 4) and Artificial Intelligence & Machine Learning (Meso Citation Topic 4.61). Relative Specialization Index (RSI) and Relative Citation Impact (RCI) indicators are calculated for 781 European NUTS-3 regions. While major metropolitan hubs such as Paris, Warszawa, and Madrid dominate in absolute publication volume, the results reveal that the highest levels of relative AI specialization are concentrated in peripheral regions, particularly in Eastern Europe and Spain. Granada and Vilniaus apskritis stand out as regions combining high specialization with strong citation visibility. The analysis further suggests a weak relationship between regional specialization and citation impact, revealing multiple regional profiles, including highly specialized regions with limited citation visibility, highly visible regions with comparatively low specialization, and diversified scientific systems combining moderate specialization with strong citation impact. Fyn emerges as an extreme case of very high citation impact despite relatively low specialization.
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