Analysis Shows Trump's Social Media Following Beat Democrats in Debate

By Wayne Rash  |  Posted 2015-10-14 Print this article Print
Debate Analysis

But it should also be noted that during the entire debate, Republican candidate Donald Trump was getting a continuous level of social media support that was higher than all of the Democratic candidate support combined. Trump made a point of live-tweeting the debates, which certainly stirred up some of his supporters. But in some cases, Trump was ahead of the Democratic line-up by an order of magnitude.

Of course we were measuring social media activity, not conducting a scientific poll, but in the previous test we found that our real-time social media results tracked very closely with the results from polling reported a few days later. For example, we saw Carly Fiorina's surge as it happened and correctly predicted that Scott Walker would withdraw from the primary, which he did a few days later.

In the Democratic contest our results also tracked well with preliminary polling. This would suggest that while Hillary Clinton remains ahead in the polls, the support for Bernie Sanders, especially when considering his lead in social media, may well help the Vermont senator gain additional voter and fundraising clout.

Perhaps more remarkable is Trump’s surge in social media support, which continues at a much higher level than any of the Democrats. If the Trump organization can leverage that sentiment and turn it into votes, then the Clinton camp, especially, has reason to worry.

As interesting as it was to use LUX2016 to predict how the debates turn out before anybody gets to see polling results, what's more interesting is its use for instant viewer sentiment analysis, which is only a minor example of what this big data analysis engine is capable of producing. While I was working with ICG Solutions CEO David Waldrop in preparing for this analysis, I got a glimpse of far greater potential than the debates.

Imagine for example that you could track every ship on every ocean in the world in real time and then using machine learning predict where that ship would be at some time in the future. This would be nice for a shipping company, obviously, but imagine using it to determine when a freighter in the Indian Ocean decides to make an unscheduled stop to deliver weapons to terrorists. You could be alerted instantly, which would be handy if you were fighting terrorism.

The fact that LUX2016 can process a nearly unlimited amount of data in real-time and analyze it according to pre-built and easily configurable rules means that this is a tool that can analyze data in ways that exceed the imagination. This goes far beyond just tracking voter sentiment and response, but even there it can make a difference.



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