What, when and where of petitions submitted to the UK government during a time of chaos

DC FieldValueLanguage
dc.contributor.authorVidgen, Bertie-
dc.contributor.authorYasseri, Taha-
dc.date.accessioned2022-01-12T13:07:28Z-
dc.date.available2022-01-12T13:07:28Z-
dc.date.copyright2020 the Authorsen_US
dc.date.issued2020-07-11-
dc.identifier.citationPolicy Sciencesen_US
dc.identifier.issn0032-2687-
dc.identifier.urihttp://hdl.handle.net/10197/12722-
dc.description.abstractIn times marked by political turbulence and uncertainty, as well as increasing divisiveness and hyperpartisanship, Governments need to use every tool at their disposal to understand and respond to the concerns of their citizens. We study issues raised by the UK public to the Government during 2015–2017 (surrounding the UK EU membership referendum), mining public opinion from a data set of 10,950 petitions, which contain 30.5 million signatures. We extract the main issues with a ground-up natural language processing method, latent Dirichlet allocation topic modelling. We then investigate their temporal dynamics and geographic features. We show that whilst the popularity of some issues is stable across the 2 years, others are highly influenced by external events, such as the referendum in June 2016. We also study the relationship between petitions’ issues and where their signatories are geographically located. We show that some issues receive support from across the whole country, but others are far more local. We then identify six distinct clusters of constituencies based on the issues which constituents sign. Finally, we validate our approach by comparing the petitions’ issues with the top issues reported in Ipsos MORI survey data. These results show the huge power of computationally analysing petitions to understand not only what issues citizens are concerned about but also when and from where.en_US
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.rightsThis 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_US
dc.subjectPetitionen_US
dc.subjectPolitical participationen_US
dc.subjectBrexiten_US
dc.subjectOpinion miningen_US
dc.subjectGovernmenten_US
dc.subjectPolitical participationen_US
dc.subjectPolicyen_US
dc.subjectAgeen_US
dc.titleWhat, when and where of petitions submitted to the UK government during a time of chaosen_US
dc.typeJournal Articleen_US
dc.internal.authorcontactothertaha.yasseri@ucd.ieen_US
dc.statusPeer revieweden_US
dc.identifier.volume53en_US
dc.identifier.issue3en_US
dc.identifier.startpage535en_US
dc.identifier.endpage557en_US
dc.identifier.doi10.1007/s11077-020-09395-y-
dc.neeo.contributorVidgen|Bertie|aut|-
dc.neeo.contributorYasseri|Taha|aut|-
dc.description.othersponsorshipEngineering and Physical Sciences Research Councilen_US
dc.description.othersponsorshipAlan Turing Instituteen_US
dc.date.updated2021-12-02T18:43:50Z-
dc.identifier.grantidEP/N510129/1-
dc.rights.licensehttps://creativecommons.org/licenses/by/3.0/ie/en_US
item.fulltextWith Fulltext-
item.grantfulltextopen-
Appears in Collections:Sociology Research Collection
Geary Institute Research Collection
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