A review on the novelty measurements of academic papers
arXiv:2501.17456 · doi:10.1007/s11192-025-05234-0
Abstract
Novelty evaluation is vital for the promotion and management of innovation. With the advancement of information techniques and the open data movement, some progress has been made in novelty measurements. Tracking and reviewing novelty measures provides a data-driven way to assess contributions, progress, and emerging directions in the science field. As academic papers serve as the primary medium for the dissemination, validation, and discussion of scientific knowledge, this review aims to offer a systematic analysis of novelty measurements for scientific papers. We began by comparing the differences between scientific novelty and four similar concepts, including originality, scientific innovation, creativity, and scientific breakthrough. Next, we reviewed the types of scientific novelty. Then, we classified existing novelty measures according to data types and reviewed the measures for each type. Subsequently, we surveyed the approaches employed in validating novelty measures and examined the current tools and datasets associated with these measures. Finally, we proposed several open issues for future studies.
References in corpus (7)
- Defining and identifying Sleeping Beauties in science
- Can ChatGPT evaluate research quality?
- Pandemics are catalysts of scientific novelty: Evidence from COVID-19
- Technological impact of biomedical research: the role of basicness and novelty
- Is Coronavirus-Related Research Becoming More Interdisciplinary? A Perspective of Co-occurrence Analysis and Diversity Measure of Scientific Articles
- Exploring the relationship between team institutional composition and novelty in academic papers based on fine-grained knowledge entities
- Novelpy: A Python package to measure novelty and disruptiveness of bibliometric and patent data