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dc.contributor.authorPark, Doheum
dc.contributor.authorNam, Juhan
dc.contributor.authorPark, Juyong
dc.date.accessioned2021-01-29T17:22:55Z
dc.date.available2021-01-29T17:22:55Z
dc.date.issued2020-01-30
dc.date.submitted2019-06-09
dc.identifier.others13688-019-0214-8
dc.identifier.other214
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/316868
dc.descriptionFunder: BK21 Plus Postgraduate Organization for Content Science
dc.description.abstractAbstract: Recent advances in the quantitative, computational methodology for the modeling and analysis of heterogeneous large-scale data are leading to new opportunities for understanding human behaviors and faculties, including creativity that drives creative enterprises such as science. While innovation is crucial for novel and influential achievements, quantifying these qualities in creative works remains a challenge. Here we present an information-theoretic framework for computing the novelty and influence of creative works based on their generation probabilities reflecting the degree of uniqueness of their elements in comparison with other works. Applying the formalism to a high-quality, large-scale data set of classical piano compositions–works of significant scientific and intellectual value–spanning several centuries of musical history, represented as symbolic progressions of chords, we find that the enterprise’s developmental history can be characterised as a dynamic process composed of the emergence of dominant, paradigmatic creative styles that define distinct historical periods. These findings can offer a new understanding of the evolution of creative enterprises based on principled measures of novelty and influence.
dc.languageen
dc.publisherSpringer Berlin Heidelberg
dc.rightsAttribution 4.0 International (CC BY 4.0)en
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en
dc.subjectRegular Article
dc.subjectNovelty
dc.subjectInfluence
dc.subjectComputational creativity
dc.subjectProbabilistic reference
dc.subjectNetwork
dc.subjectParadigm shift
dc.subjectClassical music
dc.titleNovelty and influence of creative works, and quantifying patterns of advances based on probabilistic references networks
dc.typeArticle
dc.date.updated2021-01-29T17:22:54Z
prism.issueIdentifier1
prism.publicationNameEPJ Data Science
prism.volume9
dc.identifier.doi10.17863/CAM.63981
dcterms.dateAccepted2019-11-29
rioxxterms.versionofrecord10.1140/epjds/s13688-019-0214-8
rioxxterms.versionVoR
rioxxterms.licenseref.urihttp://creativecommons.org/licenses/by/4.0/
dc.contributor.orcidPark, Juyong [0000-0003-4571-0017]
dc.identifier.eissn2193-1127
pubs.funder-project-idNational Research Foundation of Korea (NRF-2016S1A2A2911945, NRF-2016S1A3A2925033)


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Attribution 4.0 International (CC BY 4.0)
Except where otherwise noted, this item's licence is described as Attribution 4.0 International (CC BY 4.0)