Communications of the ACM
New Model Reveals Forgotten Influencers and 'Sleeping Beauties' of Science
The new model also can identify sleeping beauties, or papers that went relatively unacknowledged for years before experiencing a late burst of citations.
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Researchers at the University of Chicago's Knowledge Lab have created a computational model designed to directly measure the spread of influential ideas across scholarship and culture.
The team says the model uses both the full text of articles and external information such as author identity, affiliation, and journal reputation. Via topic modeling, the model tracks "discursive influence," or recurring words and phrases through historical texts that quantify how scholars discuss a field, instead of only their attributions.
To gauge a given paper's influence, the scientists could statistically excise it from history and see how scientific discourse would have evolved without its contribution. By training the model on text collections from computational linguistics, physics, and across science and scholarship, the researchers measure various biases and perceive patterns of influence.
The model also can identify "sleeping beauties," or papers that went relatively unacknowledged for prolonged periods before experiencing a late explosion of citations.
From UChicago News (IL)
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