SAN DIEGO, Aug. 7, 2015 /PRNewswire/ -- Emotient, which helps organizations better understand audience reactions to media, messages and experiences via proprietary emotion-reading algorithms and analytics, tonight measured the expressions of the 10 candidates on stage during the first Republican Presidential Primary Debate aired on FOX News. This is the first time emotion-reading technology has been used to analyze a Presidential Primary Debate.
Emotient's software reads the expressions of individuals and crowds to gain insights and assess authentic emotions and responses to stimuli, such as a message, a question or an exchange. The technology is able to verify whether a crowd or individual is feeling fear, contempt, disgust, joy, anger, surprise or sadness at a particular moment.
Emotient's emotion-reading algorithm measured and analyzed the faces of the debate's 10 candidates, identifying the dominant and most consistently expressed emotion of each participant during the course of the two-hour televised event. The findings include:
- Donald Trump predominantly conveyed "anger" while on camera.
- Ted Cruz's visage almost exclusively expressed "sadness" on air.
- Jeb Bush revealed a mix of "neutral", "surprise" and "joy" according to Emotient's algorithm.
- Scott Walker most predominantly displayed "neutral" and "fear" while on camera.
- Mike Huckabee exhibited a mix of "neutral" with "anger" on screen.
- Ben Carson revealed an almost equal mix of "neutral", "contempt" and "joy" while on camera.
- Marco Rubio displayed an even blend of "neutral", "surprise" and "joy" on air.
- Rand Paul expressed "neutral", "surprise" and "contempt" on screen.
- Chris Christie displayed a combination of "neutral" and "surprise" on camera.
- John Kasich was almost exclusively "neutral" according to Emotient's analysis.
About Emotient – Face Reading & Automated Expression Analysis
Emotient, Inc., is the leading authority in facial expression analysis. Emotient software translates facial expressions into actionable information that helps companies make better decisions based on audience response to media, products and experiences. Emotient facial expression technology is currently available through the EmotientAnalytics web service or the Emotient API. Automated emotion measurement can generate insights that increase revenue across many industries including advertising, media and entertainment, consumer goods, retail, enterprise sales, healthcare and education.
Emotient was founded by a team of six PhDs from the University of California, San Diego, who are the foremost experts in the application of machine learning, computer vision and cognitive science to facial behavioral analysis. Its proprietary, patented technology sets the industry standard for accuracy and real-time delivery of facial expression data and analysis. Emotient was named a Gartner 2014 Cool Vendor and was recognized as a 2015 TiE Top 50 Startup.
For more information on Emotient, please visit www.emotient.com.