The Case Study

Trump vs Cruz

Uncovering The Opinion Trend of the US Republican Primaries

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We analyze the social network of users discussing the US Primary Republican Election on Twitter during the month of April, 2016 leading to the Trump presumptive nomination. The most influential users in the network are identified and the popularity of Donald Trump and Ted Cruz among these users is measured.

Predictive Power of Influencers: Top Influencers identified by our algorithms tend to have stronger opinions than average Twitter users, and shifts in their sentiment allows us to predict election results in the primaries.

The sentiment of the entire network discussing the Primaries does not show any trend and does not predict the election results. On the hand, by following the Influencers we are able to predict the momentum gained by the Cruz campaign before its ultimate demise leading to the presumptive nomination of Donald Trump.

The Network of Influencers shown in the video clearly identifies how the Influencers drive the opinion trends. The Cruz Camp is “absorbed” by the Trump’s camp of Influencers by the end of April forecasting the end of the Cruz campaign. Combining our cutting-edge proprietary algorithm, called Collective Influence  Algorithm, for influencer detection with machine learning allows us to predict important trends before they materialize in the news. From elections to consumer products and political trends, our state of the art analytics allows companies and agencies to stay ahead of the competition. Contact us for free analytics at the cutting-edge!

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