What’s the challenge? One problem has been that traditional approaches to data investigations have been lacking the ability to handle mixed data effectively. Enterprise systems allow to search across structured and unstructured data, but just to reveal “results” in the form of – for example – blue links. And Business Intelligence systems on the other hand are great for seeing aggregates but lack the ability to search and investigate down to the single last record.

Within the context of the MixedEmotion project we’re interested in investigating the “emotions” in texts. At the core are algorithms, which extract measurements of “Emotional states” from text. The harvested emotional data can then be measured, averaged and acted upon.

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Emotion Recognition

“Real-time facial expression (emotion) recognition using a webcam.
Neutral and six universal expressions (surprise, anger, happiness, sadness, fear, disgust) are automatically recognized.”

Video source Youtube
Photo by Matthew Perkins (Flickr)