In the week leading up to 2016’s US Presidential Election, the AI system MogIA correctly predicted the election would turn in favor of Republican candidate, Donald Trump.
MogIA was developed in 2004 by Sanjiv Rai, founder of Indian start-up Genic.ai. So far, the AI system has correctly predicted the last three US elections.
MogIA works by sourcing information from various social media platforms where users engage to talk about current topics, politics included. The data points are sourced from YouTube, Facebook, and Twitter. At the end of the day, MogIA used around 20 million data points to decipher human behavior and predict a victory for Donald Trump.
Compared to Obama’s 2008 campaign, Donald Trump had a 25 percent higher voter engagement. The President-elect was an active Twitter users, and other Twitter users were willing to contribute to conversations focusing around the Trump hashtag.
Rai admits that MogIA cannot always tell the difference between a positive or a negative comment. If an online user chooses to mention the word Trump or Clinton then MogIA will take that as a sign of engagement.
Going up to the election, most major polling firms had tipped the scale in favor of Hillary Clinton, believing she was leading with a healthy margin. One of the things the election proved was that polling firms would need to adapt and include big data analyses in their future predictions.
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Based on an article by ElectronicProducts.
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