What Each Constituency Signs: The Geography of UK Parliament Petitions, 2024 to 2026

Parliamentary e-petitions record where their signatories live, which turns every petition into a map of public concern. This paper analyses the geography of the 734 petitions to the UK Parliament elected in 2024 that reached about 3,000 signatures by 2026, using 30,338,613 signatures counted in all 650 constituencies. Following an analysis plan written before any outcome was computed, I measure each petition's over- and under-signing with empirical Bayes location quotients and test four expectations. First, every one of the 734 petition maps is spatially clustered (median Moran's I = 0.48; shuffled seats give -0.00). Second, petitions about a particular place are far more concentrated than national ones: allowing for size, their excess dissimilarity is 189% higher (95% CI 71 to 389), though only ten such petitions exist. Third, seat profiles share a low-dimensional structure: two components hold 30% of the variation, the first aligned with graduate, younger and more diverse seats against older, whiter seats with a higher Reform UK vote, and both are stable across petitions created in different periods (split-half r = 0.96 and 0.96). Fourth, 2024 vote shares explain a median 26% of a petition's seat map, less than census composition in England and Wales (31%). EU petitions are under-signed where Reform UK polled strongly in every check; the planned association between immigration petitions and the Reform UK vote is fragile because the family pools petitions with opposite aims. The results describe places, not people.

Interactive version: https://maps.tristanhotham.com/petition-places/. Data and code: https://github.com/Tristan-Hotham/petition-places. Blog post: https://blog.tristanhotham.com/2026/10/31/petition-places/.

Sources: UK Parliament petitions site (Open Government Licence v3.0); 2024 general election results, Census 2021 shares and simplified boundaries via voteReproject (MIT; House of Commons Library and ONS data); constituency hexagons by Open Innovations (MIT). Text, figures and data CC BY 4.0; code MIT.