TL;DR
This paper introduces a normalization method to accurately map technological proximity from patent data, revealing clearer relationships between technologies and human inventors, and improving understanding of the technology space.
Contribution
The authors develop a novel normalization technique that removes confounding factors from patent data, enabling more accurate mapping of technological proximity.
Findings
Normalized networks are more correlated across proximity measures.
Inventors tend to work in closely related technology domains.
Firms' patent portfolios are less aligned with the normalized technology network.
Abstract
Technology is a complex system, with technologies relating to each other in a space that can be mapped as a network. The technology network's structure can reveal properties of technologies and of human behavior, if it can be mapped accurately. Technology networks have been made from patent data, using several measures of proximity. These measures, however, are influenced by factors of the patenting system that do not reflect technologies or their proximity. We introduce a method to precisely normalize out multiple impinging factors in patent data and extract the true signal of technological proximity, by comparing the empirical proximity measures with what they would be in random situations that remove the impinging factors. With this method, we created technology networks, using data from 3.9 million patents. After normalization, different measures of proximity became more correlated…
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