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

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.

Ordered Avalanches on the Bethe Lattice

“…There, however, we cannot know who passed information about the petition to whom; such data are crucial if we want infer about the network structure. We note only some evidence for the scale-free distribution of the avalanche size: [ 32 ] ( Figure 3 , right, with ), and [ 33 ] ( Figure 1 , with the related exponent depending on thresholds imposed by the governmental rules; for petitions up to 10,000 signatures and for the cumulative distribution, the authors get the value 1.42). In general, a lack of information on a real structure of network makes any comparison with experiment questionable.…”

Complex systems in the spotlight: next steps after the 2021 Nobel Prize in Physics

“…Similarly, our socio-political behavior has become more 'turbulent' due to the widespread use of social media [65], however the digital footprint that we leave on such platforms combined with computational tools and complex systems approach to characterising the hidden patterns, can provide a great opportunity for policy makers to understand and respond to social needs of the citizens they represent [66].…”

Electronic petitions in France on the material of Change.org, a non-governmental e-petition platform

“…Dans les études on attire l'attention sur le travail des ressources diverses telles que les ressources gouvernementales ou non-gouvernementales qui assurent la possibilité de déposer une pétition, on examine les particularités de l'activité de pétitions en ligne sur les ressources numériques comme Change.org [Halpin et coll., 2018], Avaaz.org [Aragón et coll., 2018], L'Initiative publique russe [Davydova et Goncharova, 2015] etc. On analyse l'activité de pétitions en ligne des habitants dans de différentes régions comme par exemple au Royaume-Uni [Vidgen et Yasseri, 2019], en Australie [Halpin et coll., 2018], en Belgique [Diaz et coll., 2008], en Russie [Davydova et Goncharova, 2015; etc.…”