Novel idea generation in social networks is optimized by exposure to a "Goldilocks" level of idea-variability.

ABSTRACT: Recent works suggest that striking a balance between maximizing idea stimulation and minimizing idea redundancy can elevate novel idea generation performances in self-organizing social networks. We explore whether dispersing the visibility of high-performing idea generators can help achieve such a trade-off. We employ popularity signals (follower counts) of participants as an external source of variation in network structures, which we control across four conditions in a randomized setting. We observe that popularity signals influence inspiration-seeking ties, partly by biasing people's perception of their peers' novel idea-generation performances. Networks that partially disperse the top ideators' visibility using this external signal show reduced idea redundancy and elevated idea-generat

SUBMITTER: Baten RA 

PROVIDER: S-EPMC9802244 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature