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.

通过文本挖掘和网络分析的创新方法，研究了技术联系对行业创新能力的影响以及这些影响是如何通过技术空间传递的。通过分析美国专利商标局授予的 650 万项专利的文本，并应用网络分析，对半个世纪（从 1976 年到 2021 年）间的各个行业之间的技术相互依赖进行了研究。研究发现专利文本中蕴含了大量信息，传统的创新指标（如专利引用）无法捕捉。通过网络分析，证明间接联系与直接联系同等重要，而采用更传统的间接联系的衡量方法（如 Leontief 逆矩阵）无法完全揭示这种间接联系。最后，通过脉冲响应分析，展示了技术冲击如何通过技术网络空间传递，影响行业的创新能力。