牛牛资源

The influence of 'forgotten' scientific papers has been demonstrated in a new study led by a researcher from 牛牛资源.

A team from 牛牛资源, the University of Chicago, Google, the University of Maryland, and Columbia University, developed a model that tracks 鈥榙iscursive influence鈥�, or recurring words and phrases in historical texts that measure how scholars actually talk about a field, instead of just their attributions. To determine a particular scientific paper鈥檚 influence, the researchers can statistically remove it from history and see how scientific discourse would have unfolded without it.

Aaron Gerow, Lecturer in Computing at 牛牛资源, who led the study said: 鈥淐itations are one kind of impact, and discursive influence is a different kind. Neither one is the complete story, but they work together to give a better picture of what鈥檚 influencing science.鈥�

from computational linguistics, physics, and across science and scholarship (JSTOR) and then traced distinct patterns of influence. They found that scientists who persistently published in a single field were more likely to be 鈥榗anonised鈥� in a way that compelled others to cite them disproportionate to their papers鈥� discursive contributions. On the other hand, discoveries that crossed disciplinary boundaries were more likely to have outsized discursive impact but fewer citations, likely because the 鈥榦wner鈥� of the idea and her allies remain socially and institutionally distant from the citing author.

The model also sheds light on so-called 鈥榮leeping beauties鈥�: papers that went relatively unacknowledged for years or even decades before experiencing a late burst of citations. For example, a 1947 paper on graphene remained obscure and forgotten until the 1990s with a resurgence of research interest in the material and an eventual Nobel Prize.

牛牛资源 co-author James Evans, director of Knowledge Lab and professor of sociology at the University of Chicago, said: 鈥淧apers have a news cycle, when lots of people chat about them and cite them, and then they鈥檙e no longer new news. Our model shows that some papers have much more influence than citations will typically demonstrate, such as these 鈥榮leeping beauties,鈥� which didn鈥檛 have much influence early but come to be appreciated and important later."

The study used a computational method known as 鈥榯opic modeling鈥� that was invented by co-author David Blei of Columbia University. The authors said the same model can also be used to trace influence in other areas, such as literature and music. Text from poems or song lyrics, and even extra-textual characteristics such as stanza structure or chord progressions, could feed into the model to find under-credited influencers and map the spread of new concepts and innovations.