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dc.contributor.authorBotta, F
dc.contributor.authorPreis, T
dc.contributor.authorMoat, HS
dc.date.accessioned2020-07-23T09:23:15Z
dc.date.issued2020-06-05
dc.description.abstractMeasuring collective human behaviour has traditionally been a time-consuming and expensive process, impairing the speed at which data can be made available to decision makers in policy. Can data generated through widespread use of online services help provide faster insights? Here, we consider an example relating to policymaking for culture and the arts: publicly funded museums and galleries in the UK. We show that data on Google searches for museums and galleries can be used to generate estimates of their visitor numbers. Crucially, we find that these estimates can be generated faster than traditional measurements, thus offering policymakers early insights into changes in cultural participation supported by public funds. Our findings provide further evidence that data on our use of online services can help generate timely indicators of changes in society, so that decision makers can focus on the present rather than the past.en_GB
dc.description.sponsorshipESRCen_GB
dc.description.sponsorshipAlan Turing Instituteen_GB
dc.description.sponsorshipEPSRCen_GB
dc.identifier.citationVol. 9 Article number: 14en_GB
dc.identifier.doi10.1140/epjds/s13688-020-00232-z
dc.identifier.grantnumberES/M500434/1en_GB
dc.identifier.grantnumberEP/N510129/1en_GB
dc.identifier.grantnumberTU/B/000008en_GB
dc.identifier.grantnumberTU/B/000006en_GB
dc.identifier.urihttp://hdl.handle.net/10871/122097
dc.language.isoenen_GB
dc.publisherEDP Sciencesen_GB
dc.rights(c) the Authors. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.en_GB
dc.subjectCultureen_GB
dc.subjectmobilityen_GB
dc.subjectonline dataen_GB
dc.subjectFaster indicatorsen_GB
dc.subjectNowcastingen_GB
dc.titleIn search of art: rapid estimates of gallery and museum visits using Google Trendsen_GB
dc.typeArticleen_GB
dc.date.available2020-07-23T09:23:15Z
dc.descriptionThis is the final version. Available from EDP Sciences via the DOI in this record. en_GB
dc.descriptionAll data sets are publicly available through the DCMS website [38] and Google Trends [50].en_GB
dc.identifier.eissn2193-1127
dc.identifier.journalEPJ Data Scienceen_GB
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/.en_GB
dcterms.dateAccepted2020-05-24
rioxxterms.versionVoRen_GB
rioxxterms.licenseref.startdate2020-05-24
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2020-07-23T09:19:17Z
refterms.versionFCDVoR
refterms.dateFOA2020-07-23T09:23:22Z
refterms.panelBen_GB


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(c) the Authors. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
Except where otherwise noted, this item's licence is described as (c) the Authors. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.