'Automating the Boring Stuff' with Pollfinder.ai

When an election season ramps up, newsrooms turn to polls to get a better understanding of both the state of the race and Americans’ attitudes about what’s on the ballot. These polls give journalists a sense of whether an upstart progressive has a shot at being the next mayor of New York or whether involving the US military in strikes against Iran might be unpopular among President Trump’s supporters.

But turning polls into meaningful insight isn’t straightforward. For instance, while one recent poll shows a progressive candidate within arm’s reach of winning the Democratic primary for mayor in New York City, an overview of all of the polls about the race gives a more complete picture of just how close he may be. But aggregating polling data and interpreting it, however, is a laborious process that requires a specialized skillset: fluency in statistics, an understanding of the political polling landscape, and a daily commitment to finding, reading and standardizing new data. Highly skilled researchers in newsrooms that aggregate polls often spend hours on rote tasks just to keep the data-pipelines running.