Mapping Social Media Interest in 2016 Presidential Candidates

As poll after poll emerges from the morass of political dark waters, we often find ourselves confused about the truth of the 2016 Presidential race. The traditional source of truth in campaigning, polling, has become difficult to trust due to low response rates and otherwise poor results, but is so far without replacement. Further, the aim of traditional polling is to predict results using demographics and surveys, when what pollsters are really looking for is support within specific geographic boundaries. Much like in commercial site selection, campaigns are turning to social media and big data to develop a clear image of their base.

We at IdealSpot have developed a tool to do exactly that. By applying our Customer Location Targeting to the most popular 2016 presidential candidates (as of the time of writing), we are able to map the interest of voters in our hometown of Austin, TX. These maps represent the number of people who have expressed explicit interest in each candidate, whether that be through visiting a social media profile, clicking an ad, or searching for related terms. The darkest outlined regions represent locations with the densest support of each candidate, while the lightest regions are the least dense. Click each image to get a better look.

Hillary Clinton support in Austin (range: 52 to 68,438 people)

Bernie Sanders support in Austin (range: 34 to 210,366 people)

Donald Trump support in Austin (range: 30 to 47,580 people)

Ted Cruz support in Austin (range: 48 to 30,383 people)

Austin is often considered a liberal city, but as we see here that is not entirely the case. Downtown Austin is definitely feeling the Bern, but suburbs and surrounding towns like Round Rock and Buda express more interest in the GOP. South of Sunset Valley (in the Slaughter Lane area) we see a region of contention between all candidates. We invite you to explore correlations with variables like age, net worth, and education using our free demographic overlays