Knowledge transfer by universities is a top priority in innovation policy and a primary purpose for public research funding, due to being an important driver of technical change and innovation. Current empirical research on the impact of university research relies mainly on formal databases and indicators such as patents, collaborative publications and license agreements, to assess the contribution to the socioeconomic surrounding of universities. In this study, we present an extension of the current empirical framework by applying new computational methods, namely text mining and pattern recognition. Text samples for this purpose can include files containing social media contents, company websites and annual reports. The empirical focus in the present study is on the technical sciences and in particular on the case of the Technical University of Denmark (DTU). We generated two independent text collections (corpora) to identify correlations of university publications and company webpages. One corpus representing the company sites, serving as sample of the private economy and a second corpus, providing the reference to the university research, containing relevant publications. We associated the former with the latter to obtain insights into possible text and semantic relatedness. The text mining methods are extrapolating the correlations, semantic patterns and content comparison of the two corpora to define the document relatedness. We expect the development of a novel tool using contemporary techniques for the measurement of public research impact. The approach aims to be applicable across universities and thus enable a more holistic comparable assessment. This rely less on formal databases, which is certainly beneficial in terms of the data reliability. We seek to provide a supplementary perspective for the detection of the dissemination of university research and hereby enable policy makers to gain additional insights of (informal) contributions of knowledge dissemination by universities.
|Title of host publication||Proceedings of the 21st international conference on Science and Technology Indicators (STI 2016)|
|Number of pages||5|
|Publication status||Published - 2016|
|Event||21st international conference on Science and Technology Indicators (STI 2016) - València, Spain|
Duration: 14 Sep 2016 → 16 Sep 2016
Conference number: 21
|Conference||21st international conference on Science and Technology Indicators (STI 2016)|
|Period||14/09/2016 → 16/09/2016|
Bibliographical noteThis work is licensed under a Creative Commons License: Attribution-NonCommercial-NoDerivatives 4.0 International.
Woltmann, S., Clemmensen, L. K. H., & Alkærsig, L. (2016). From university research to innovation Detecting knowledge transfer via text mining. In Proceedings of the 21st international conference on Science and Technology Indicators (STI 2016)