Boyd-Graber Publishes Paper in PNAS that Assesses Scholarly Influence

Jordan Boyd-Graber, an associate professor of computer science with appointments in UMIACS, the iSchool and the Language Science Center, recently had a paper accepted to the journal Proceedings of the National Academy of Sciences.

“Measuring discursive influence across scholarship” examines what aspects of a piece of research (topic, researchers, institution) are most likely to impact the way other scientists do science.

Boyd-Graber co-authored the paper with Yuening Hu, a research scientist at Google Cloud who received her doctoral degree in computer science at UMD, along with collaborators from the University of Chicago and Columbia University.

As part of their work in assessing scholarly influence, the researchers performed in-depth analyses on collections of physics research (500,000 abstracts; 102 years) and scholarship generally (JSTOR repository: two million full-text articles; 130 years).

One goal of this research, the authors say, is that it can help reveal signals that will recognize authors who make diverse contributions—and whose contributions may take longer to be appreciated—thus allowing fellow academics to compensate for traditional measures of productivity like citation count, which can be biased by field or personality.