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Insights on the Road to 2020
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ALY 6110 - Final Project - Kriegbaum & Bajak.pdf

Insights on the Road to 2020

Measuring the Effect of a Fox News Appearance for 2020 Democratic Candidates based on Google Trends

The field of Democratic candidates running for U.S. president in 2020 is sprawling. With 24 and counting, American voters are overwhelmed by the sheer size of the field, and many of the candidates struggle to achieve any kind of name recognition. Most candidates are currently polling around 1%, and some likely won’t make it onto the debate stages at the end of June 2019.

That’s what’s made the offers from Fox News for candidates to join their anchors onstage for a town hall discussion increasingly appealing. While some Democrats, like Elizabeth Warren and Kamala Harris, have flat out rejected their invitations, others have gladly accepted. Those appearing are likely hoping that the highly popular right-leaning television network will help boost their name recognition and drum up interest across a broader spectrum of Americans.

So the question we have is simple: Are these Fox News appearances effective in generating interest? If they are, how did candidates benefit, and who benefited the most?

We posit that by tapping into the vast amounts of data generated by Google searches, we might be able to gauge the interest of Google-using Americans towards the candidates. Using Google Trends, we pulled historical search data for three candidates that had already appeared on the network and began our search for indicators that might help us gauge any changes in interest. We settled on using related search terms for each candidate, the associated geographical information from searches, and search interest over time in order to form our understanding about the potential value of a Fox News appearance.

We chose three 2020 candidates, Bernie Sanders, Pete Buttigieg and Kirsten Gillibrand, who attended a Town Hall style forum on Fox News in April, May and June, respectively. Using the whole names for each candidate as the main search term, or ‘keyword,’ we used the R package, “gtrendsR,” to create a master record of all search data across those months.

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