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来源类型 | Working Paper |
规范类型 | 报告 |
DOI | 10.3386/w27803 |
来源ID | Working Paper 27803 |
Linguistic Metrics for Patent Disclosure: Evidence from University Versus Corporate Patents | |
Nancy Kong; Uwe Dulleck; Adam B. Jaffe; Shupeng Sun; Sowmya Vajjala | |
发表日期 | 2020-09-14 |
出版年 | 2020 |
语种 | 英语 |
摘要 | This paper proposes a novel approach to measure disclosure in patent applications using algorithms from computational linguistics. Borrowing methods from the literature on second language acquisition, we analyze core linguistic features of 40,949 U.S. applications in three patent categories related to nanotechnology, batteries, and electricity from 2000 to 2019. Relying on the expectation that universities have more incentives to disclose their inventions than corporations for either incentive reasons or for different source documents that patent attorneys can draw on, we confirm the relevance and usefulness of the linguistic measures by showing that university patents are more readable. Combining the multiple measures using principal component analysis, we find that the gap in disclosure is 0.4 SD, with a wider gap between top applicants. Our results do not change after accounting for the heterogeneity of inventions by controlling for cited-patent fixed effects. We also explore whether one pathway by which corporate patents become less readable is use of multiple examples to mask the “best mode” of inventions. By confirming that computational linguistic measures are useful indicators of readability of patents, we suggest that the disclosure function of patents can be explored empirically in a way that has not previously been feasible. |
主题 | Development and Growth ; Innovation and R& ; D |
URL | https://www.nber.org/papers/w27803 |
来源智库 | National Bureau of Economic Research (United States) |
引用统计 | |
资源类型 | 智库出版物 |
条目标识符 | http://119.78.100.153/handle/2XGU8XDN/585475 |
推荐引用方式 GB/T 7714 | Nancy Kong,Uwe Dulleck,Adam B. Jaffe,et al. Linguistic Metrics for Patent Disclosure: Evidence from University Versus Corporate Patents. 2020. |
条目包含的文件 | ||||||
文件名称/大小 | 资源类型 | 版本类型 | 开放类型 | 使用许可 | ||
w27803.pdf(311KB) | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 |
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