Exploring Novelty Differences between Industry and Academia: A Knowledge Entity-centric Perspective

Novel ideas drive innovation, and both academia and industry possess distinct strengths in advancing technological progress. The industrial sector, on the one hand, seeks to privatize knowledge to maintain appropriability, while on the other hand, it actively promotes open-sourcing of models and platform sharing. This paradox raises the question of whether industrial disclosures are less novel compared to those from academia. Some studies argue that academia tends to generate more novel ideas, while others suggest that industry researchers are more likely to drive new breakthroughs. Previous studies have been limited by data sources and inconsistent measures of novelty. To address these gaps, thisstudy establishes a unified framework for calculating the novelty of papers and patent data in the field of Natural Language Processing (NLP), focusing on fine-grained knowledge entities. Additionally, a regression model is constructed to analyse the relationship between the type of institution and the novelty of their publications. The results show that academia demonstrates higher novelty in both patent and paper outputs. Notably, academic involvement significantly enhances the novelty of industrial patents. Furthermore, this study examines how team size impacts novelty in patents and papers, providing strategic recommendations for forming research teams. We release our data and associated codes at https://github.com/tinierZhao/entity_novelty.