science as a giant conscious hive mind

In a new article in Social Networks, Feng Shi, Jacob Foster, and James Evans argued that the complexity and diversity of scientific semantic networks creates very high rates of innovation. From Weaving the fabric of science: Dynamic network models of science’s unfolding structure:

Science is a complex system. Building on Latour’s actor network theory, we model published science as a dynamic hypergraph and explore how this fabric provides a substrate for future scientific discovery. Using millions of abstracts from MEDLINE, we show that the network distance between biomedical things (i.e., people, methods, diseases, chemicals) is surprisingly small. We then show how science moves from questions answered in one year to problems investigated in the next through a weighted random walk model. Our analysis reveals intriguing modal dispositions in the way biomedical science evolves: methods play a bridging role and things of one type connect through things of another. This has the methodological implication that adding more node types to network models of science and other creative domains will likely lead to a superlinear increase in prediction and understanding.

Bringing soc of science and network analysis together. Love it.

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Written by fabiorojas

June 12, 2015 at 12:01 am

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