Which technological linkages affect the sector's ability to innovate? How do these effects transmit through the technology space? This paper answers these two key questions using novel methods of text mining and network analysis. We examine technological interdependence across sectors over a period of half a century (from 1976 to 2021) by analyzing the text of 6.5 million patents granted by the United States Patent and Trademark Office (USPTO), and applying network analysis to uncover the full spectrum of linkages existing across technology areas. We demonstrate that patent text contains a wealth of information often not captured by traditional innovation metrics, such as patent citations. By using network analysis, we document that indirect linkages are as important as direct connections and that the former would remain mostly hidden using more traditional measures of indirect linkages, such as the Leontief inverse matrix. Finally, based on an impulse-response analysis, we illustrate how technological shocks transmit through the technology (network-based) space, affecting the innovation capacity of the sectors.

翻译：哪些技术联系会影响产业的创新能力？这些效应如何在技术空间中传导？本文运用文本挖掘与网络分析的新方法，对以上两个关键问题展开研究。我们通过分析美国专利商标局（USPTO）授权的650万件专利文本，并运用网络分析方法揭示技术领域间存在的全部关联谱系，考察了半个世纪（1976年至2021年）跨产业的技术相互依赖关系。研究表明，专利文本包含大量传统创新指标（如专利引文）未能捕捉的信息。通过网络分析，我们证实间接联系与直接联系同等重要，且前者在使用列昂惕夫逆矩阵等传统间接联系测度方法时基本处于隐匿状态。最后，基于脉冲响应分析，我们阐释了技术冲击如何通过（基于网络的）技术空间进行传导，进而影响各产业的创新能力。