Disclosure in patents, an economic analysis using computational linguistics

Project dates: 01/02/2018 - Ongoing

This project aims to analyse the disclosure of patents. To achieve economic growth, the patent system aims to provide incentives for research and development as well as to ensure knowledge is accessible as widely as possible.

Why is this important?

Intellectual property (IP) is an important tool for economic growth. Patents are a form of IP that grant the owner a monopoly over an invention. Developed to encourage innovation, in return for making a full disclosure of a new invention, a patent provides a legal right to exclude others from using the invention. However, the balance between encouraging and stifling innovation is fine with the scope of exclusivity granted by patents often misaligned with the increment of the invention. From a policy perspective a patent system that promotes, rather than hinders, innovation is essential to foster economic growth.

What we aim to do

This project will explore and demonstrate the usefulness of computational linguistics in the economic analysis of disclosure in patents. In particular, the project will look at the role of readability in the patent application and examination process. This will provide a strong potential to inform and improve patent examination processes and patent policy. Expected outcomes will enable society to achieve greater use of the knowledge embedded in the patent system, thereby contributing to higher economic growth.


For more information about this project please email best@qut.edu.au 

Funding / Grants

  • Funded by ARC DP180103856

Chief Investigators


Other Team Members

  • Dr Sowmya Balakrishna – Iowa State University
  • Prof Adam Jaffe – New Zealand Motu Economic and Public Policy Research Institute


  • Jefferson, Osmat Azzam, Jaffe, Adam, Ashton, Doug, Warren, Ben, Koellhofer, Deniz, Dulleck, Uwe, Ballagh, Aaron, Moe, John, DiCuccio, Michael, Ward, Karl, et al. (2018) Mapping the global influence of published research on industry and innovation. Nature Biotechnology, 36, pp.31-39.

Rich Media

  • Linguistic Metrics for Patent Disclosure: Evidence from University Versus Corporate Patents – Working Paper