Using big data to study small places: Small‐town voting patterns in the 2020 U.S. presidential election

Abstract

AbstractDifferences between urban, suburban, and rural voting outcomes in U.S. presidential elections is a common area of both academic research and news media analysis. Most scrutiny and mapping of the geography of the presidential vote is done at the county scale, with counties described as either urban, suburban, or rural. Small towns are often assumed to mirror surrounding rural areas, with little research examining election results and historic patterns in these places. This is understandable: Accurate spatial data at a fine scale for national elections is difficult and, in some states, impossible, to obtain. Research presented here (in states where precinct‐level data is readily available) indicates that while most small towns indeed voted Republican in the 2020 U.S. election, a closer inspection indicates that they are more Democratic‐leaning than surrounding rural areas. This research indicates the value of studying these fine‐scale data as well as the challenges faced in acquiring these data and resulting lack of research and visualization of these differences.