How VERN gets the feels-The differences between sentiment analysis and emotion recognition. Pt. 4 of 4

In part 4 and the final video of our four part series, VERN CEO Craig Tucker brings it all back together: How this all fits in the model VERN uses to detect emotions. Through contextual clues, frames of reference and moderating by the personal frame VERN is able to detect emotions.

Craig illustrates the power of VERN’s patented method like a trip to the eye doctor: Each lens focusses the concept to be clear the end user, like VERN uses their patented personal frames. He explains where emotions come from, and what they’re made of: Emotives. Emotives are words and phrases that are known to impart emotional meaning. VERN tracks these emotives and provides a confidence score of 0-100{b1ba36726a3bfcdc42af6e5ec24af305dbc6425c95dfb7052d7f2b4aabbf1a02}. Each additional emotive signal adds to the confidence level, and intensity of the found emotion.

We finish by inviting you all to join the Virtual Emotion Resource Network, and help us discover new emotions and possibly reach a consensus on something that’s universal to all of us: Our feelings.