What can artificial intelligence tell us about the climate town hall?
Resonate uses AI machine learning and best-in-class survey research paired with trackable online and offline behaviors to reveal a holistic view of the American voter, which is a critical component heading into an already high-stakes 2020 election season. We published Resonate Candidate Index values for the presidential debates in Miami, Detroit and Houston, which shows the lift or decline in viewings of favorable content about candidates based on online behavior in the five days prior to, and five days following, the debate (or even weeks later).
The Resonate Candidate index measures the amount of positive web pages that are browsed by the American voting public. It does so anonymously, never violating user privacy, and it shows a clear picture of how Americans are interacting with content all over the web. Resonate anonymously analyzes 10 billion daily online events on more than 550 million devices across 2 trillion words on 35,000 topics. While the Resonate Candidate Index has been accurate in predicting the rise and fall of specific candidates after the Democratic presidential debates, let’s examine how it works with something a bit less formal.
The Resonate Candidate Index also tracks responses to news events
In this presidential candidate analysis, we used the CNN Climate Town Hall as a benchmark, and measured five days of web browsing both before and after that event. So, who moved the needle?
According to the Resonate Candidate Index, Kamala Harris and Marianne Williamson saw the biggest increase in positive online engagement after the climate town hall. Positive online engagement surrounding Harris increased by 576% after the debate. Marianne Williamson, although she came from a low base of support, saw an increase of 518% in positive engagement following the event. Other big winners included Pete Buttigieg, who saw an increase of 375% in positive online engagement, and the resurrection of New York mayor Bill DeBlasio, who saw an increase of 298%.
Overall, the biggest net positive movers after the CNN Climate Town Hall were as follows:
And who were the biggest losers at the CNN Climate Town Hall?
How will machine learning play out in the 2020 election?
In the past, the Resonate Candidate Index has proven a useful tool in gauging post-debate lift or decline in how the voting public positively engages with a presidential candidate.
Stay with Resonate throughout the 2020 election season for real-time, AI-driven updates on the Resonate Candidate Index. Our next post-debate engagement check-in will be five days following the next Democratic debates in October. AI-driven predictive analytics help campaigns discover voter segments that the traditional voter file and third-party data analysis could never find.
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