Using a machine learning technique called cluster analysis and publicly available data from the N.C. Board of Elections and Ethics Enforcement, UNC masters student Scott Smith turned the state’s nearly 3,000 voting precincts from the 2016 election into seven distinct types of voting communities in North Carolina.
First in our series of posts that help you navigate the pitfalls you’ll come across when analyzing North Carolina’s voting and elections data. In our first installment, we have what appears in the database to be North Carolinians with amazingly long lives and one voter who seems to have traveled in time. Spoiler alert: neither are what they appear to be.
The goal of this new project is to help make the power of voting and election data in North Carolina more accessible to journalists and everyday citizens. Here’s what we’ve done so far and what we’re planning to do. Please come along for the ride!