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dc.contributor.authorYu, Zhao
dc.contributor.authorRonen, Shahar
dc.contributor.authorHu, Kevin
dc.contributor.authorLu, Tiffany T.
dc.contributor.authorHidalgo Ramaciotti, Cesar A.
dc.date.accessioned2017-12-12T15:54:10Z
dc.date.available2017-12-12T15:54:10Z
dc.date.issued2016-01
dc.date.submitted2015-02
dc.identifier.issn2052-4463
dc.identifier.urihttp://hdl.handle.net/1721.1/112710
dc.description.abstractWe present the Pantheon 1.0 dataset: a manually verified dataset of individuals that have transcended linguistic, temporal, and geographic boundaries. The Pantheon 1.0 dataset includes the 11,341 biographies present in more than 25 languages in Wikipedia and is enriched with: (i) manually verified demographic information (place and date of birth, gender) (ii) a taxonomy of occupations classifying each biography at three levels of aggregation and (iii) two measures of global popularity including the number of languages in which a biography is present in Wikipedia (L), and the Historical Popularity Index (HPI) a metric that combines information on L, time since birth, and page-views (2008-2013). We compare the Pantheon 1.0 dataset to data from the 2003 book, Human Accomplishments, and also to external measures of accomplishment in individual games and sports: Tennis, Swimming, Car Racing, and Chess. In all of these cases we find that measures of popularity (L and HPI) correlate highly with individual accomplishment, suggesting that measures of global popularity proxy the historical impact of individuals.en_US
dc.publisherNature Publishing Groupen_US
dc.relation.isversionofhttp://dx.doi.org/10.1038/SDATA.2015.75en_US
dc.rightsCreative Commons Attribution 4.0 Internationalen_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.sourceNatureen_US
dc.titlePantheon 1.0, a manually verified dataset of globally famous biographiesen_US
dc.typeArticleen_US
dc.identifier.citationYu, Amy Zhao et al. “Pantheon 1.0, a Manually Verified Dataset of Globally Famous Biographies.” Scientific Data 3 (January 2016): 150075 © 2016 The Author(s)en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.contributor.departmentMassachusetts Institute of Technology. Media Laboratoryen_US
dc.contributor.mitauthorYu, Zhao
dc.contributor.mitauthorRonen, Shahar
dc.contributor.mitauthorHu, Kevin
dc.contributor.mitauthorLu, Tiffany T.
dc.contributor.mitauthorHidalgo Ramaciotti, Cesar A.
dc.relation.journalScientific Dataen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2017-12-11T17:47:17Z
dspace.orderedauthorsYu, Amy Zhao; Ronen, Shahar; Hu, Kevin; Lu, Tiffany; Hidalgo, César A.en_US
dspace.embargo.termsNen_US
dc.identifier.orcidhttps://orcid.org/0000-0002-1731-0377
dc.identifier.orcidhttps://orcid.org/0000-0002-6765-168X
dc.identifier.orcidhttps://orcid.org/0000-0001-7616-9441
dc.identifier.orcidhttps://orcid.org/0000-0002-6031-5982
mit.licensePUBLISHER_CCen_US


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