The Network Structure Of Collective Innovation
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Degree type
Doctor of Philosophy (PhD)
Graduate group
Communication
Discipline
Subject
computational social science
data science
experiment
network structure
Communication
data science
experiment
network structure
Communication
Funder
Grant number
License
Copyright date
2018-02-23T20:17:00-08:00
Distributor
Related resources
Author
Contributor
Abstract
Prior research on how to design collaboration networks among scientists, engineers, and strategists surprisingly predicts that inefficient networks that slow down the rate of collaboration will lead to better performance on complex problems. However, empirical research has provided mixed evidence for these ideas. Here, we test this theory using an online Data Science Competition that experimentally manipulates the network efficiency of teams working on a complex problem. The results support the idea that less efficient collaboration networks increase collective performance on complex problems. The results have important implications for designing problem-solving teams in numerous domains.
Advisor
Damon Centola
Date of degree
2017-01-01