Science and Technology Advance through Surprise

Shi, Feng, Evans, James

arXiv.org Machine Learning 

Figure 4 (left) shows that the probability of being a hit paper increases gradually with career and team novelty, but expedition novelty rises much more quickly as the strongest predictor. Papers involving the most unexpected publication events or conversations are 3.5 times more likely than random to be hit papers. Figure 4 (left) also shows that career and team novelties are highly correlated, suggesting that successful teams not only have members from multiple disciplines, but also members with diverse backgrounds who "glue" interdisciplinary teams together (also see Figure S3). Successful knowledge expeditions, however, are the most likely path associated with breakthrough discovery. When regressing content and context novelties of a paper separately on the three background novelty measures, we find that expedition novelty has by far the largest effect on context novelty (), but team novelty has the marginal top effect on . 2 3, p 0 0 1 β 2 .

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