@article{8a70fc96cb384350a2ca44bf55a06e90,
title = "Linguistic metrics for patent disclosure: Evidence from university versus corporate patents",
abstract = "Encouraging disclosure is important for the patent system, yet the technical information in patent applications is often inadequate. We use algorithms from computational linguistics to quantify the effectiveness of disclosure in patent applications. Relying on the expectation that universities have more ability and incentive to disclose their inventions than corporations, we analyze 64 linguistic measures of patent applications, and show that university patents are more readable by 0.4 SD of a synthetic measure of readability. Results are robust to controlling for non-disclosure-related invention heterogeneity. The linguistic metrics are evaluated by a panel of “expert” student engineers and further examined by USPTO 112(a) – lack of disclosure – rejection. The ability to quantify disclosure opens new research paths and potentially facilitates improvement of disclosure.",
keywords = "Computational linguistic analysis, Corporate patents, Patent disclosure, Readability, University patents",
author = "Nancy Kong and Uwe Dulleck and Jaffe, {Adam B.} and Shupeng Sun and Sowmya Vajjala",
note = "Funding Information: We thank Andrew A. Toole (Chief Economist of The US Patent and Trademark Office), Nicholas Pairolero (USPTO), Lisa Larrimore Ouellette, Heidi Williams, Monika Schnitzer, Mike Teodorescu, Lesley Millar-Nicholson (Director of The Technology Licensing Office, MIT), and Timothy Oyer (President of Wolf Greenfield Intellectual Property Law), as well as participants at the Innovation Information Initiative Technical Working Group, Chief Economist Speaker Series at USPTO, Technology & Policy Research Initiative IP day at Boston University, and Queensland University of Technology. We appreciate Hamish Macintosh and Yi Wang for their technical support. This research uses data from the Lens ( https://www.lens.org/ ), and we are grateful to Richard Jefferson and Aaron Ballagh for their constructive comments and data support. This project is funded by Australian Research Council Discovery Grant DP180103856 . Funding Information: We thank Andrew A. Toole (Chief Economist of The US Patent and Trademark Office), Nicholas Pairolero (USPTO), Lisa Larrimore Ouellette, Heidi Williams, Monika Schnitzer, Mike Teodorescu, Lesley Millar-Nicholson (Director of The Technology Licensing Office, MIT), and Timothy Oyer (President of Wolf Greenfield Intellectual Property Law), as well as participants at the Innovation Information Initiative Technical Working Group, Chief Economist Speaker Series at USPTO, Technology & Policy Research Initiative IP day at Boston University, and Queensland University of Technology. We appreciate Hamish Macintosh and Yi Wang for their technical support. This research uses data from the Lens (https://www.lens.org/), and we are grateful to Richard Jefferson and Aaron Ballagh for their constructive comments and data support. This project is funded by Australian Research Council Discovery Grant DP180103856. Publisher Copyright: {\textcopyright} 2022",
year = "2022",
month = dec,
doi = "10.1016/j.respol.2022.104670",
language = "English",
volume = "52",
pages = "1--21",
journal = "Research Policy",
issn = "0048-7333",
publisher = "Elsevier",
number = "2",
}