Memo to President Obama and his successors: Big Data analysis suggests you should keep your State of the Union speeches positive -- regardless of the geopolitical climate during each speech.

The evidence comes from Northwestern University graduate students Zach Anglin and Shawn Li. The duo, participating in a big data and analytics hackathon, took a close look at all State of the Union addresses to analyze textual content.

Based on the analytics, the two grad students reached this conclusion: Positive U.S. presidential addresses resulted in higher popularity and approval ratings -- whatever the country's problems at the time.

The second place team, Paul Jennings and Ye Tu, analyzed Amazon.com reviews to identify instances of Internet bot reviews posing as authentic customers, the University said.

The April 29 Hackathon was led by Teradata team members and Northwestern Professor Diego Klabjan in the context of the university's Master of Science in Analytics Program. Thirty-six graduate students in Northwestern's Data Sciences curriculum showcased their data science skills, competing to resolve complex problems using analytical techniques such as pattern recognition, text analysis, graph analytics and predictive computation, the university said.

The Hackathon leveraged Teradata's Aster Discovery Platform, an analytic engine designed for big data sets, to solve complex hypothetical problems in such areas as social network analysis, fraud detection, supply chain management, text analysis and money laundering.

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