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What, when and where of petitions submitted to the UK government during a time of chaos
Author(s)
Date Issued
2020-07-11
Date Available
2022-01-12T13:07:28Z
Abstract
In 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.
Other Sponsorship
Engineering and Physical Sciences Research Council
Alan Turing Institute
Type of Material
Journal Article
Publisher
Springer
Journal
Policy Sciences
Volume
53
Issue
3
Start Page
535
End Page
557
Copyright (Published Version)
2020 the Authors
Language
English
Status of Item
Peer reviewed
ISSN
0032-2687
This item is made available under a Creative Commons License
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