Science advances through evolution with an intermittent revolution. Breakthroughs, such as examinations of markets in the presence of information asymmetry, the development of laser-based precision spectroscopy, and cell reprogramming, have a long-lasting impact and trigger new areas of research. 
A commonly asked question is which fields actively produce high-impact research and how the field's ability to be at the forefront of the research enterprise changes over time. To answer this, there first needs to be a way to reliably identify high-impact publications. The impact has long been approximated using citation data, capturing the volume of subsequent work a certain paper or discovery induces. Consequently, the raw number of citations, C, garnered by a paper is arguably the most widely used indicator for impact. However, C suffers from two well-studied biases: i) temporal bias, as reflected by the higher rate of citations accumulated by papers published later rooted in the inflation of citations over time, hence making it difficult to compare the impact of older papers with more recent ones; and ii) field bias, manifested by systematic differences of C across disciplines creates the impression that papers in highly cited fields, like cell biology, have bigger impact than mathematics papers, where citations are fewer.
Technology Overview
In this invention, Northeastern University researchers propose a new indicator to quantify the impact of a publication. The indicator automatically identifies the field of a paper through its co-cited papers and normalizes its yearly impact with respect to the impact obtained by papers in the field, therefore not requiring a priori discipline label of papers. Applying the measure to papers published in 63 years shows that it follows a universal distribution for papers across time and is not susceptible to field bias. Using this indicator can quantify temporal dynamics of the production of high impact works across disciplines and identify several fields, such as geosciences, radiology, and optics, that have been sources of breakthroughs. This work provides insights into the evolution of science and paves a way for fair comparisons of the impact of diverse entities in the scientific enterprise.
- Fast to calculate
- Better ranking of the impact of papers than existing methods
- Able to compare impact of scientists, journals, institutions, or other types of entities in different disciplines and time
- Identifying important genes that may be responsible for phenotypes of interest
- Identifying and recommending influential users in online social networks (Facebook, Twitter)
- Identifying important chemicals that may be associated with diseases of interest
- License
- Partnering
- Research collaboration
Patent Information:
1. Life Science
For Information, Contact:
Mark Saulich
Associate Director of Commercialization
Northeastern University
Qing Ke
Albert-Laszlo Barabasi